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Home           Papers           Datasets           Metrics           

Home           Alphabetical           Year           Application           Task           Annotation           

A-D           E-I           J-Z           

A-D

    20BN link paper arxiv
    • Summary: A dataset of 220K+ videos of 174 different activities
    • Applications: Video prediction
    • Data type and annotations: RGB, Activity Label
    • Task: Activity
      Used in papers
        Rothfuss et al., "Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution", RAL, 2018. paper arxiv
          Datasets Metrics
          Bibtex 
          @Article{Rothfuss_2018_RAL,
    author = "Rothfuss, J. and Ferreira, F. and Aksoy, E. E. and Zhou, Y. and Asfour, T.",
    journal = "RAL",
    title = "Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution",
    year = "2018",
    volume = "3",
    number = "4",
    pages = "4007-4014"
}
      Bibtex 
      @InProceedings{Goyal_2017_ICCV,
    author = "Goyal, Raghav and Kahou, Samira Ebrahimi and Michalski, Vincent and Materzynska, Joanna and Westphal, Susanne and Kim, Heuna and Haenel, Valentin and Fruend, Ingo and Yianilos, Peter and Mueller-Freitag, Moritz and others",
    title = "The Something Something Video Database for Learning and Evaluating Visual Common Sense.",
    booktitle = "ICCV",
    year = "2017"
}
    3D Movie link
    • Summary: A dataset of annotated poses and stereo pairs.
    • Applications: Other prediction
    • Data type and annotations: RGB, 3D Pose, Stereo
    • Task: Pose
      Used in papers
        Lin et al., "Predictive Feature Learning for Future Segmentation Prediction", ICCV, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Lin_2021_ICCV,
    author = "Lin, Zihang and Sun, Jiangxin and Hu, Jian-Fang and Yu, Qizhi and Lai, Jian-Huang and Zheng, Wei-Shi",
    title = "Predictive Feature Learning for Future Segmentation Prediction",
    booktitle = "ICCV",
    year = "2021"
}
      Bibtex 
      @inproceedings{Alahari_2013_ICCV,
    author = "Alahari, Karteek and Seguin, Guillaume and Sivic, Josef and Laptev, Ivan",
    title = "Pose Estimation and Segmentation of People in {3D} Movies",
    booktitle = "ICCV",
    year = "2013"
}
    3D POSES IN THE WILD (3DPW) link paper
    • Summary: A dataset of 60 video sequences with 2D poses and 3D body models
    • Applications: Motion prediction
    • Data type and annotations: RGB, 2D/3D pose, models
    • Task: Outdoor
      Used in papers
        Adeli et al., "TRiPOD: Human Trajectory and Pose Dynamics Forecasting in the Wild", ICCV, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Adeli_2021_ICCV,
    author = "Adeli, Vida and Ehsanpour, Mahsa and Reid, Ian and Niebles, Juan Carlos and Savarese, Silvio and Adeli, Ehsan and Rezatofighi, Hamid",
    title = "{TRiPOD}: Human Trajectory and Pose Dynamics Forecasting in the Wild",
    booktitle = "ICCV",
    year = "2021"
}
        Sun et al., "MoML: Online Meta Adaptation for 3D Human Motion Prediction", CVPR, 2024. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Sun_MoML_2024_CVPR,
    author = "Sun, Xiaoning and Sun, Huaijiang and Li, Bin and Wei, Dong and Li, Weiqing and Lu, Jianfeng",
    title = "MoML: Online Meta Adaptation for 3D Human Motion Prediction",
    booktitle = "CVPR",
    year = "2024"
}
        Chen et al., "Rethinking Human Motion Prediction with Symplectic Integral", CVPR, 2024. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Chen_Rethinking_2024_CVPR,
    author = "Chen, Haipeng and Lyu, Kedi and Liu, Zhenguang and Yin, Yifang and Yang, Xun and Lyu, Yingda",
    title = "Rethinking Human Motion Prediction with Symplectic Integral",
    booktitle = "CVPR",
    year = "2024"
}
        Jeong et al., "Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning", CVPR, 2024. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Jeong_Multi_2024_CVPR,
    author = "Jeong, Jaewoo and Park, Daehee and Yoon, Kuk-Jin",
    title = "Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning",
    booktitle = "CVPR",
    year = "2024"
}
        Gao et al., "Decompose More and Aggregate Better: Two Closer Looks at Frequency Representation Learning for Human Motion Prediction", CVPR, 2023. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Gao_2023_CVPR,
    author = "Gao, Xuehao and Du, Shaoyi and Wu, Yang and Yang, Yang",
    title = "Decompose More and Aggregate Better: Two Closer Looks at Frequency Representation Learning for Human Motion Prediction",
    booktitle = "CVPR",
    year = "2023"
}
        Peng et al., "Trajectory-Aware Body Interaction Transformer for Multi-Person Pose Forecasting", CVPR, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Peng_2023_CVPR,
    author = "Peng, Xiaogang and Mao, Siyuan and Wu, Zizhao",
    title = "Trajectory-Aware Body Interaction Transformer for Multi-Person Pose Forecasting",
    booktitle = "CVPR",
    year = "2023"
}
        Tanke et al., "Social Diffusion: Long-term Multiple Human Motion Anticipation", ICCV, 2023. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Tanke_2023_ICCV,
    author = "Tanke, Julian and Zhang, Linguang and Zhao, Amy and Tang, Chengcheng and Cai, Yujun and Wang, Lezi and Wu, Po-Chen and Gall, Juergen and Keskin, Cem",
    title = "Social Diffusion: Long-term Multiple Human Motion Anticipation",
    booktitle = "ICCV",
    year = "2023"
}
        Xu et al., "Joint-Relation Transformer for Multi-Person Motion Prediction", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Xu_2023_ICCV,
    author = "Xu, Qingyao and Mao, Weibo and Gong, Jingze and Xu, Chenxin and Chen, Siheng and Xie, Weidi and Zhang, Ya and Wang, Yanfeng",
    title = "Joint-Relation Transformer for Multi-Person Motion Prediction",
    booktitle = "ICCV",
    year = "2023"
}
        Xu et al., "Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Xu_2023_ICCV_1,
    author = "Xu, Chenxin and Tan, Robby T. and Tan, Yuhong and Chen, Siheng and Wang, Xinchao and Wang, Yanfeng",
    title = "Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction",
    booktitle = "ICCV",
    year = "2023"
}
        Saadatnejad et al., "A generic diffusion-based approach for 3D human pose prediction in the wild", ICRA, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Saadatnejad_2023_ICRA,
    author = "Saadatnejad, Saeed and Rasekh, Ali and Mofayezi, Mohammadreza and Medghalchi, Yasamin and Rajabzadeh, Sara and Mordan, Taylor and Alahi, Alexandre",
    title = "A generic diffusion-based approach for 3D human pose prediction in the wild",
    booktitle = "ICRA",
    year = "2023"
}
        Guo et al., "Back to MLP: A Simple Baseline for Human Motion Prediction", WACV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Guo_2023_WACV,
    author = "Guo, Wen and Du, Yuming and Shen, Xi and Lepetit, Vincent and Alameda-Pineda, Xavier and Moreno-Noguer, Francesc",
    title = "Back to MLP: A Simple Baseline for Human Motion Prediction",
    booktitle = "WACV",
    year = "2023"
}
        Ma et al., "Progressively Generating Better Initial Guesses Towards Next Stages for High-Quality Human Motion Prediction", CVPR, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Ma_2022_CVPR,
    author = "Ma, Tiezheng and Nie, Yongwei and Long, Chengjiang and Zhang, Qing and Li, Guiqing",
    title = "Progressively Generating Better Initial Guesses Towards Next Stages for High-Quality Human Motion Prediction",
    booktitle = "CVPR",
    year = "2022"
}
        Zhong et al., "Spatio-Temporal Gating-Adjacency GCN for Human Motion Prediction", CVPR, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhong_2022_CVPR,
    author = "Zhong, Chongyang and Hu, Lei and Zhang, Zihao and Ye, Yongjing and Xia, Shihong",
    title = "Spatio-Temporal Gating-Adjacency {GCN} for Human Motion Prediction",
    booktitle = "CVPR",
    year = "2022"
}
        Li et al., "Skeleton-Parted Graph Scattering Networks for 3D Human Motion Prediction", ECCV, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Li_2022_ECCV,
    author = "Li, Maosen and Chen, Siheng and Zhang, Zijing and Xie, Lingxi and Tian, Qi and Zhang, Ya",
    title = "Skeleton-Parted Graph Scattering Networks for {3D} Human Motion Prediction",
    booktitle = "ECCV",
    year = "2022"
}
        Sun et al., "Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction", ECCV, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Sun_2022_ECCV,
    author = "Sun, Xiaoning and Cui, Qiongjie and Sun, Huaijiang and Li, Bin and Li, Weiqing and Lu, Jianfeng",
    title = "Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction",
    booktitle = "ECCV",
    year = "2022"
}
        Wang et al., "Multi-Person 3D Motion Prediction with Multi-Range Transformers", NeurIPS, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Wang_2021_NeurIPS,
    author = "Wang, Jiashun and Xu, Huazhe and Narasimhan, Medhini and Wang, Xiaolong",
    booktitle = "NeurIPS",
    title = "Multi-Person {3D} Motion Prediction with Multi-Range Transformers",
    year = "2021"
}
        Cui et al., "Towards Accurate 3D Human Motion Prediction From Incomplete Observations", CVPR, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Cui_2021_CVPR,
    author = "Cui, Qiongjie and Sun, Huaijiang",
    title = "Towards Accurate {3D} Human Motion Prediction From Incomplete Observations",
    booktitle = "CVPR",
    year = "2021"
}
        Sofianos et al., "Space-Time-Separable Graph Convolutional Network for Pose Forecasting", ICCV, 2021. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Sofianos_2021_ICCV,
    author = "Sofianos, Theodoros and Sampieri, Alessio and Franco, Luca and Galasso, Fabio",
    title = "Space-Time-Separable Graph Convolutional Network for Pose Forecasting",
    booktitle = "ICCV",
    year = "2021"
}
        Cui et al., "Learning Dynamic Relationships for 3D Human Motion Prediction", CVPR, 2020. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Cui_2020_CVPR,
    author = "Cui, Qiongjie and Sun, Huaijiang and Yang, Fei",
    title = "Learning Dynamic Relationships for 3D Human Motion Prediction",
    booktitle = "CVPR",
    year = "2020"
}
        Mao et al., "History Repeats Itself: Human Motion Prediction via Motion Attention", ECCV, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Mao_2020_ECCV,
    author = "Mao, Wei and Liu, Miaomiao and Salzmann, Mathieu",
    title = "History Repeats Itself: Human Motion Prediction via Motion Attention",
    booktitle = "ECCV",
    year = "2020"
}
        Chao et al., "Adversarial Refinement Network for Human Motion Prediction", ACCV, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Chao_2020_ACCV,
    author = "Chao, Xianjin and Bin, Yanrui and Chu, Wenqing and Cao, Xuan and Ge, Yanhao and Wang, Chengjie and Li, Jilin and Huang, Feiyue and Leung, Howard",
    title = "Adversarial Refinement Network for Human Motion Prediction",
    booktitle = "ACCV",
    year = "2020"
}
        Lebailly et al., "Motion Prediction Using Temporal Inception Module", ACCV, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Lebailly_2020_ACCV,
    author = "Lebailly, Tim and Kiciroglu, Sena and Salzmann, Mathieu and Fua, Pascal and Wang, Wei",
    title = "Motion Prediction Using Temporal Inception Module",
    booktitle = "ACCV",
    year = "2020"
}
        Mao et al., "Learning Trajectory Dependencies For Human Motion Prediction", ICCV, 2019. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Mao_2019_ICCV,
    author = "Mao, Wei and Liu, Miaomiao and Salzmann, Mathieu and Li, Hongdong",
    title = "Learning Trajectory Dependencies For Human Motion Prediction",
    booktitle = "ICCV",
    year = "2019"
}
      Bibtex 
      @InProceedings{vonMarcard_2018_ECCV,
    author = "von Marcard, Timo and Henschel, Roberto and Black, Michael and Rosenhahn, Bodo and Pons-Moll, Gerard",
    title = "Recovering Accurate {3D} Human Pose In The Wild Using {IMUs} And A Moving Camera",
    booktitle = "ECCV",
    year = "2018"
}
    3DSSG link paper
    • Summary: A dataset of 482 scene graphs consisting of 48k object nodes and 544k edges.
    • Applications:
    • Data type and annotations: Graph, Attributes, 3D Scan
    • Task: Objects
      Used in papers
        Looper et al., "3D VSG: Long-term Semantic Scene Change Prediction through 3D Variable Scene Graphs", ICRA, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Looper_2023_ICRA,
    author = "Looper, Samuel and Rodriguez-Puigvert, Javier and Siegwart, Roland and Cadena, Cesar and Schmid, Lukas",
    title = "3D VSG: Long-term Semantic Scene Change Prediction through 3D Variable Scene Graphs",
    booktitle = "ICRA",
    year = "2023"
}
      Bibtex 
      @InProceedings{Wald_2020_CVPR,
    author = "Wald, Johanna and Dhamo, Helisa and Navab, Nassir and Tombari, Federico",
    title = "Learning 3D Semantic Scene Graphs from 3D Indoor Reconstructions",
    booktitle = "CVPR",
    year = "2020"
}
    3RScan link paper arxiv
    • Summary: A dataset of real-world objects with 1482 3D reconstructions / snapshots of 478 naturally changing indoor environments.
    • Applications:
    • Data type and annotations: 3D Scan, RGBD
    • Task: Objects
      Used in papers
        Looper et al., "3D VSG: Long-term Semantic Scene Change Prediction through 3D Variable Scene Graphs", ICRA, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Looper_2023_ICRA,
    author = "Looper, Samuel and Rodriguez-Puigvert, Javier and Siegwart, Roland and Cadena, Cesar and Schmid, Lukas",
    title = "3D VSG: Long-term Semantic Scene Change Prediction through 3D Variable Scene Graphs",
    booktitle = "ICRA",
    year = "2023"
}
      Bibtex 
      @InProceedings{Wald_2019_ICCV,
    author = "Wald, Johanna and Avetisyan, Armen and Navab, Nassir and Tombari, Federico and Niessner, Matthias",
    title = "RIO: 3D Object Instance Re-Localization in Changing Indoor Environments",
    booktitle = "ICCV",
    year = "2019"
}
    50Salads link paper
    • Summary: A dataset of 25 human subjects preparing 2 mixed salads each with 4h+ of annotated accelerometer and RGB-D video data recorded 50hz and 30hz respectively
    • Applications: Action prediction
    • Data type and annotations: RGBD, activity label, temporal segment, accelerometer
    • Task: Cooking (egocentric)
      Used in papers
        Guo et al., "Uncertainty-aware Action Decoupling Transformer for Action Anticipation", CVPR, 2024. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Guo_Uncertainty_2024_CVPR,
    author = "Guo, Hongji and Agarwal, Nakul and Lo, Shao-Yuan and Lee, Kwonjoon and Ji, Qiang",
    title = "Uncertainty-aware Action Decoupling Transformer for Action Anticipation",
    booktitle = "CVPR",
    year = "2024"
}
        Girase et al., "Latency Matters: Real-Time Action Forecasting Transformer", CVPR, 2023. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Girase_2023_CVPR,
    author = "Girase, Harshayu and Agarwal, Nakul and Choi, Chiho and Mangalam, Karttikeya",
    title = "Latency Matters: Real-Time Action Forecasting Transformer",
    booktitle = "CVPR",
    year = "2023"
}
        Nawhal et al., "Rethinking Learning Approaches for Long-Term Action Anticipation", ECCV, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Nawhal_2022_ECCV,
    author = "Nawhal, Megha and Jyothi, Akash Abdu and Mori, Greg",
    title = "Rethinking Learning Approaches for Long-Term Action Anticipation",
    booktitle = "ECCV",
    year = "2022"
}
        Roy et al., "Action Anticipation Using Latent Goal Learning", WACV, 2022. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Roy_2022_WACV,
    author = "Roy, Debaditya and Fernando, Basura",
    title = "Action Anticipation Using Latent Goal Learning",
    booktitle = "WACV",
    year = "2022"
}
        Ke et al., "Future Moment Assessment for Action Query", WACV, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Ke_2021_WACV,
    author = "Ke, Qiuhong and Fritz, Mario and Schiele, Bernt",
    title = "Future Moment Assessment for Action Query",
    booktitle = "WACV",
    year = "2021"
}
        Piergiovanni et al., "Adversarial Generative Grammars for Human Activity Prediction", ECCV, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Piergiovanni_2020_ECCV,
    author = "Piergiovanni, AJ and Angelova, Anelia and Toshev, Alexander and Ryoo, Michael S",
    title = "Adversarial Generative Grammars for Human Activity Prediction",
    booktitle = "ECCV",
    year = "2020"
}
        Zhao et al., "On Diverse Asynchronous Activity Anticipation", ECCV, 2020. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhao_2020_ECCV,
    author = "Zhao, He and Wildes, Richard P.",
    title = "On Diverse Asynchronous Activity Anticipation",
    booktitle = "ECCV",
    year = "2020"
}
        Ke et al., "Time-Conditioned Action Anticipation In One Shot", CVPR, 2019. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Ke_2019_CVPR,
    author = "Ke, Qiuhong and Fritz, Mario and Schiele, Bernt",
    title = "Time-Conditioned Action Anticipation In One Shot",
    booktitle = "CVPR",
    year = "2019"
}
        Gammulle et al., "Forecasting Future Action Sequences With Neural Memory Networks", BMVC, 2019. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Gammulle_2019_BMVC,
    author = "Gammulle, Harshala and Denman, Simon and Sridharan, Sridha and Fookes, Clinton",
    title = "Forecasting Future Action Sequences With Neural Memory Networks",
    year = "2019",
    booktitle = "BMVC"
}
        Abu et al., "When Will You Do What? - Anticipating Temporal Occurrences Of Activities", CVPR, 2018. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Farha_2018_CVPR,
    author = "Abu Farha, Yazan and Richard, Alexander and Gall, Juergen",
    title = "When Will You Do What? - Anticipating Temporal Occurrences Of Activities",
    booktitle = "CVPR",
    year = "2018"
}
      Bibtex 
      @InProceedings{Stein_2013_IJCPUC,
    author = "Stein, Sebastian and McKenna, Stephen J",
    title = "Combining Embedded Accelerometers With Computer Vision For Recognizing Food Preparation Activities",
    booktitle = "UbiComp",
    year = "2013"
}
    ACTICIPATE link paper arxiv
    • Summary: A collection of datasets for human-robot interaction involving object handover between humans and human-robots
    • Applications: Action prediction
    • Data type and annotations: RGB, gaze, pose
    • Task: Interaction
      Used in papers
        Schydlo et al., "Anticipation In Human-Robot Cooperation: A Recurrent Neural Network Approach For Multiple Action Sequences Prediction", ICRA, 2018. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Schydlo_2018_ICRA_2,
    author = "Schydlo, P. and Rakovic, M. and Jamone, L. and Santos-Victor, J.",
    booktitle = "ICRA",
    title = "Anticipation In Human-Robot Cooperation: A Recurrent Neural Network Approach For Multiple Action Sequences Prediction",
    year = "2018"
}
      Bibtex 
      @InProceedings{Schydlo_2018_ICRA,
    author = "Schydlo, Paul and Rakovic, Mirko and Jamone, Lorenzo and Santos-Victor, Jos{\'e}",
    title = "Anticipation In Human-Robot Cooperation: A Recurrent Neural Network Approach For Multiple Action Sequences Prediction",
    booktitle = "ICRA",
    year = "2018"
}
    ActivityNet link paper
    • Summary: A dataset of 648 hours of video with 100 videos per 200 different activity classes
    • Applications: Video prediction
    • Data type and annotations: RGB, Activity Label
    • Task: Activity
      Used in papers
        Rothfuss et al., "Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution", RAL, 2018. paper arxiv
          Datasets Metrics
          Bibtex 
          @Article{Rothfuss_2018_RAL,
    author = "Rothfuss, J. and Ferreira, F. and Aksoy, E. E. and Zhou, Y. and Asfour, T.",
    journal = "RAL",
    title = "Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution",
    year = "2018",
    volume = "3",
    number = "4",
    pages = "4007-4014"
}
        Hosseinzadeh et al., "Video Captioning of Future Frames", WACV, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Hosseinzadeh_2021_WACV,
    author = "Hosseinzadeh, Mehrdad and Wang, Yang",
    title = "Video Captioning of Future Frames",
    booktitle = "WACV",
    year = "2021"
}
      Bibtex 
      @InProceedings{Caba_2015_CVPR,
    author = "Fabian Caba Heilbron, Victor Escorcia, Bernard Ghanem and Niebles, Juan Carlos",
    title = "{ActivityNet}: A Large-Scale Video Benchmark for Human Activity Understanding",
    booktitle = "CVPR",
    year = "2015"
}
    Amazon link paper arxiv
    • Summary: A dataset of 142M+ product reviews from Amazon with corresponding metadata including price, brand, descriptions, category information, etc.
    • Applications: Other prediction
    • Data type and annotations: Features, attribute, text
    • Task: Fashion
      Used in papers
        Al-Halah et al., "Fashion Forward: Forecasting Visual Style In Fashion", ICCV, 2017. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Al-Halah_2017_ICCV,
    author = "Al-Halah, Ziad and Stiefelhagen, Rainer and Grauman, Kristen",
    title = "Fashion Forward: Forecasting Visual Style In Fashion",
    booktitle = "ICCV",
    year = "2017"
}
      Bibtex 
      @InProceedings{Mcauley_2015_CRDIR,
    author = "McAuley, Julian and Targett, Christopher and Shi, Qinfeng and Van Den Hengel, Anton",
    title = "Image-Based Recommendations On Styles And Substitutes",
    booktitle = "SIGIR",
    year = "2015"
}
    AMOS link paper
    • Summary: A dataset of 17M+ images captured every half hour during a period of 6 months from 538 outdoor webcams across the US
    • Applications: Other prediction
    • Data type and annotations: RGB, time, camera coordinate
    • Task: Weather
      Used in papers
        Chu et al., "Visual Weather Temperature Prediction", WACV, 2018. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Chu_2018_WACV,
    author = "Chu, W. and Ho, K. and Borji, A.",
    booktitle = "WACV",
    title = "Visual Weather Temperature Prediction",
    year = "2018"
}
      Bibtex 
      @InProceedings{Jacobs_2007_CVPR,
    author = "Jacobs, Nathan and Roman, Nathaniel and Pless, Robert",
    title = "Consistent Temporal Variations In Many Outdoor Scenes",
    booktitle = "CVPR",
    year = "2007"
}
    AnAn Accident Detection (A3D) link paper arxiv
    • Summary: A dataset of 1500 video clips of traffic accidents with start and end annotations of events
    • Applications: Trajectory prediction
    • Data type and annotations: RGB, Temporal segment
    • Task: Driving
      Used in papers
        Yao et al., "Unsupervised Traffic Accident Detection in First-Person Videos", IROS, 2019. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Yao_2019_IROS,
    author = "Yao, Y. and Xu, M. and Wang, Y. and Crandall, D. J. and Atkins, E. M.",
    booktitle = "IROS",
    title = "Unsupervised Traffic Accident Detection in First-Person Videos",
    year = "2019"
}
      Bibtex 
      @InProceedings{Yao_2019_IROS,
    author = "Yao, Y. and Xu, M. and Wang, Y. and Crandall, D. J. and Atkins, E. M.",
    booktitle = "IROS",
    title = "Unsupervised Traffic Accident Detection in First-Person Videos",
    year = "2019"
}
    ApolloScape link paper arxiv
    • Summary: A driving dataset of 5K vehicle instances, 110K lane segments and 100 mins of sequences for trajectory prediction and tracking annotated at 2hz
    • Applications: Trajectory prediction
    • Data type and annotations: Stereo RGB, LIDAR, 3D Bounding Box, Object Class, Semantic Segment, Tracking ID
    • Task: Driving
      Used in papers
        Zhang et al., "On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles", CVPR, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhang_2022_CVPR,
    author = "Zhang, Qingzhao and Hu, Shengtuo and Sun, Jiachen and Chen, Qi Alfred and Mao, Z. Morley",
    title = "On Adversarial Robustness of Trajectory Prediction for Autonomous Vehicles",
    booktitle = "CVPR",
    year = "2022"
}
        Zhang et al., "D2-TPred: Discontinuous Dependency for Trajectory Prediction under Traffic Lights", ECCV, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhang_2022_ECCV,
    author = "Zhang, Yuzhen and Wang, Wentong and Guo, Weizhi and Lv, Pei and Xu, Mingliang and Chen, Wei and Manocha, Dinesh",
    title = "{D2-TPred}: Discontinuous Dependency for Trajectory Prediction under Traffic Lights",
    booktitle = "ECCV",
    year = "2022"
}
        Zheng et al., "Unlimited Neighborhood Interaction for Heterogeneous Trajectory Prediction", ICCV, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zheng_2021_ICCV,
    author = "Zheng, Fang and Wang, Le and Zhou, Sanping and Tang, Wei and Niu, Zhenxing and Zheng, Nanning and Hua, Gang",
    title = "Unlimited Neighborhood Interaction for Heterogeneous Trajectory Prediction",
    booktitle = "ICCV",
    year = "2021"
}
        Wang et al., "Multiple Contextual Cues Integrated Trajectory Prediction for Autonomous Driving", RAL, 2021. paper
          Datasets Metrics
          Bibtex 
          @Article{Wang_2021_RAL,
    author = "Wang, Li and Wu, Tao and Fu, Hao and Xiao, Liang and Wang, Zhiyu and Dai, Bin",
    journal = "RAL",
    title = "Multiple Contextual Cues Integrated Trajectory Prediction for Autonomous Driving",
    year = "2021",
    volume = "6",
    number = "4",
    pages = "6844-6851"
}
        Fang et al., "TPNet: Trajectory Proposal Network for Motion Prediction", CVPR, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Fang_2020_CVPR,
    author = "Fang, Liangji and Jiang, Qinhong and Shi, Jianping and Zhou, Bolei",
    title = "{TPNet}: Trajectory Proposal Network for Motion Prediction",
    booktitle = "CVPR",
    year = "2020"
}
        He et al., "UST: Unifying Spatio-Temporal Context for Trajectory Prediction in Autonomous Driving", IROS, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{He_2020_IROS,
    author = "He, H. and Dai, H. and Wang, N.",
    booktitle = "IROS",
    title = "UST: Unifying Spatio-Temporal Context for Trajectory Prediction in Autonomous Driving",
    year = "2020"
}
        Chandra et al., "Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs", RAL, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @Article{Chandra_2020_RAL,
    author = "Chandra, R. and Guan, T. and Panuganti, S. and Mittal, T. and Bhattacharya, U. and Bera, A. and Manocha, D.",
    journal = "RAL",
    title = "Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in {Graph-LSTMs}",
    year = "2020",
    volume = "5",
    number = "3",
    pages = "4882-4890"
}
      Bibtex 
      @article{Wang_2019_PAMI,
    author = "Wang, Peng and Huang, Xinyu and Cheng, Xinjing and Zhou, Dingfu and Geng, Qichuan and Yang, Ruigang",
    title = "The {ApolloScape} Open Dataset for Autonomous Driving and its Application",
    journal = "PAMI",
    year = "2019"
}
    Archive of Motion Capture as Surface Shapes (AMASS) link paper arxiv
    • Summary: A dataset of 40 hours of video recording of 300 subjects with more than 11K motions
    • Applications: Motion prediction
    • Data type and annotations: RGB, 3D Model
    • Task: Activity
      Used in papers
        Tian et al., "TransFusion: A Practical and Effective Transformer-Based Diffusion Model for 3D Human Motion Prediction", RAL, 2024. paper code
          Datasets Metrics
          Bibtex 
          @ARTICLE{Tian_TransFusion_2024_RAL,
    author = "Tian, Sibo and Zheng, Minghui and Liang, Xiao",
    journal = "RAL",
    title = "TransFusion: A Practical and Effective Transformer-Based Diffusion Model for 3D Human Motion Prediction",
    year = "2024",
    volume = "9",
    number = "7",
    pages = "6232-6239"
}
        Barquero et al., "BeLFusion: Latent Diffusion for Behavior-Driven Human Motion Prediction", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Barquero_2023_ICCV,
    author = "Barquero, German and Escalera, Sergio and Palmero, Cristina",
    title = "BeLFusion: Latent Diffusion for Behavior-Driven Human Motion Prediction",
    booktitle = "ICCV",
    year = "2023"
}
        Chen et al., "HumanMAC: Masked Motion Completion for Human Motion Prediction", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Chen_2023_ICCV_1,
    author = "Chen, Ling-Hao and Zhang, JiaWei and Li, Yewen and Pang, Yiren and Xia, Xiaobo and Liu, Tongliang",
    title = "HumanMAC: Masked Motion Completion for Human Motion Prediction",
    booktitle = "ICCV",
    year = "2023"
}
        Saadatnejad et al., "A generic diffusion-based approach for 3D human pose prediction in the wild", ICRA, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Saadatnejad_2023_ICRA,
    author = "Saadatnejad, Saeed and Rasekh, Ali and Mofayezi, Mohammadreza and Medghalchi, Yasamin and Rajabzadeh, Sara and Mordan, Taylor and Alahi, Alexandre",
    title = "A generic diffusion-based approach for 3D human pose prediction in the wild",
    booktitle = "ICRA",
    year = "2023"
}
        Kedia et al., "ManiCast: Collaborative Manipulation with Cost-Aware Human Forecasting", CoRL, 2023. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Kushal_2023_CoRL,
    author = "Kedia, Kushal and Dan, Prithwish and Bhardwaj, Atiksh and Choudhury, Sanjiban",
    title = "ManiCast: Collaborative Manipulation with Cost-Aware Human Forecasting",
    booktitle = "CoRL",
    year = "2023"
}
        Guo et al., "Back to MLP: A Simple Baseline for Human Motion Prediction", WACV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Guo_2023_WACV,
    author = "Guo, Wen and Du, Yuming and Shen, Xi and Lepetit, Vincent and Alameda-Pineda, Xavier and Moreno-Noguer, Francesc",
    title = "Back to MLP: A Simple Baseline for Human Motion Prediction",
    booktitle = "WACV",
    year = "2023"
}
        Salzmann et al., "Motron: Multimodal Probabilistic Human Motion Forecasting", CVPR, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Salzmann_2022_CVPR,
    author = "Salzmann, Tim and Pavone, Marco and Ryll, Markus",
    title = "Motron: Multimodal Probabilistic Human Motion Forecasting",
    booktitle = "CVPR",
    year = "2022"
}
        Zhong et al., "Spatio-Temporal Gating-Adjacency GCN for Human Motion Prediction", CVPR, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhong_2022_CVPR,
    author = "Zhong, Chongyang and Hu, Lei and Zhang, Zihao and Ye, Yongjing and Xia, Shihong",
    title = "Spatio-Temporal Gating-Adjacency {GCN} for Human Motion Prediction",
    booktitle = "CVPR",
    year = "2022"
}
        Zhang et al., "We Are More Than Our Joints: Predicting How 3D Bodies Move", CVPR, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhang_2021_CVPR,
    author = "Zhang, Yan and Black, Michael J. and Tang, Siyu",
    title = "We Are More Than Our Joints: Predicting How {3D} Bodies Move",
    booktitle = "CVPR",
    year = "2021"
}
        Sofianos et al., "Space-Time-Separable Graph Convolutional Network for Pose Forecasting", ICCV, 2021. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Sofianos_2021_ICCV,
    author = "Sofianos, Theodoros and Sampieri, Alessio and Franco, Luca and Galasso, Fabio",
    title = "Space-Time-Separable Graph Convolutional Network for Pose Forecasting",
    booktitle = "ICCV",
    year = "2021"
}
        Mao et al., "History Repeats Itself: Human Motion Prediction via Motion Attention", ECCV, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Mao_2020_ECCV,
    author = "Mao, Wei and Liu, Miaomiao and Salzmann, Mathieu",
    title = "History Repeats Itself: Human Motion Prediction via Motion Attention",
    booktitle = "ECCV",
    year = "2020"
}
      Bibtex 
      @InProceedings{Mahmood_2019_ICCV,
    author = "Mahmood, Naureen and Ghorbani, Nima and Troje, Nikolaus F. and Pons-Moll, Gerard and Black, Michael J.",
    title = "{AMASS}: Archive of Motion Capture as Surface Shapes",
    booktitle = "ICCV",
    year = "2019"
}
    Argoverse link paper arxiv
    • Summary: A dataset with 100+ driving segments and 10K+ 3D bounding boxes for tracking and 300K+ segments for forecasting annotated at 10hz
    • Applications: Trajectory prediction
    • Data type and annotations: RGB, LIDAR, 3D bounding box, Map, Trajectory
    • Task: Driving
      Used in papers
        Jiao et al., "TAE: A Semi-supervised Controllable Behavior-aware Trajectory Generator and Predictor", IROS, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Jiao_2022_IROS,
    author = "Jiao, Ruochen and Liu, Xiangguo and Zheng, Bowen and Liang, Dave and Zhu, Qi",
    booktitle = "IROS",
    title = "{TAE}: A Semi-supervised Controllable Behavior-aware Trajectory Generator and Predictor",
    year = "2022"
}
        Zaech et al., "Action Sequence Predictions of Vehicles in Urban Environments using Map and Social Context", IROS, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zaech_2020_IROS,
    author = "Zaech, J. -N. and Dai, D. and Liniger, A. and Gool, L. V.",
    booktitle = "IROS",
    title = "Action Sequence Predictions of Vehicles in Urban Environments using Map and Social Context",
    year = "2020"
}
        Zhou et al., "SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction", CVPR, 2024. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhou_SmartRefine_2024_CVPR,
    author = "Zhou, Yang and Shao, Hao and Wang, Letian and Waslander, Steven L. and Li, Hongsheng and Liu, Yu",
    title = "SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction",
    booktitle = "CVPR",
    year = "2024"
}
        Xu et al., "Adapting to Length Shift: FlexiLength Network for Trajectory Prediction", CVPR, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Xu_Adapting_2024_CVPR,
    author = "Xu, Yi and Fu, Yun",
    title = "Adapting to Length Shift: FlexiLength Network for Trajectory Prediction",
    booktitle = "CVPR",
    year = "2024"
}
        Tang et al., "HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention", CVPR, 2024. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Tang_HPNet_2024_CVPR,
    author = "Tang, Xiaolong and Kan, Meina and Shan, Shiguang and Ji, Zhilong and Bai, Jinfeng and Chen, Xilin",
    title = "HPNet: Dynamic Trajectory Forecasting with Historical Prediction Attention",
    booktitle = "CVPR",
    year = "2024"
}
        Pourkeshavarz et al., "Adversarial Backdoor Attack by Naturalistic Data Poisoning on Trajectory Prediction in Autonomous Driving", CVPR, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Pourkeshavarz_Adversarial_2024_CVPR,
    author = "Pourkeshavarz, Mozhgan and Sabokrou, Mohammad and Rasouli, Amir",
    title = "Adversarial Backdoor Attack by Naturalistic Data Poisoning on Trajectory Prediction in Autonomous Driving",
    booktitle = "CVPR",
    year = "2024"
}
        Wen et al., "Density-Adaptive Model Based on Motif Matrix for Multi-Agent Trajectory Prediction", CVPR, 2024. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Wen_Density_2024_CVPR,
    author = "Wen, Di and Xu, Haoran and He, Zhaocheng and Wu, Zhe and Tan, Guang and Peng, Peixi",
    title = "Density-Adaptive Model Based on Motif Matrix for Multi-Agent Trajectory Prediction",
    booktitle = "CVPR",
    year = "2024"
}
        Lu et al., "Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture", CVPR, 2024. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Lu_Quantifying_2024_CVPR,
    author = "Lu, Juanwu and Cui, Can and Ma, Yunsheng and Bera, Aniket and Wang, Ziran",
    title = "Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture",
    booktitle = "CVPR",
    year = "2024"
}
        Pourkeshavarz et al., "CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving", CVPR, 2024. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Pourkeshavarz_CaDeT_2024_CVPR,
    author = "Pourkeshavarz, Mozhgan and Zhang, Junrui and Rasouli, Amir",
    title = "CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving",
    booktitle = "CVPR",
    year = "2024"
}
        Lan et al., "SEPT: Towards Efficient Scene Representation Learning for Motion Prediction", ICLR, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @inproceedings{Lan_SEPT_2024_ICLR,
    author = "Lan, Zhiqian and Jiang, Yuxuan and Mu, Yao and Chen, Chen and Li, Shengbo Eben",
    title = "{SEPT}: Towards Efficient Scene Representation Learning for Motion Prediction",
    booktitle = "ICLR",
    year = "2024"
}
        Karim et al., "DESTINE: Dynamic Goal Queries with Temporal Transductive Alignment for Trajectory Prediction", ICRA, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @inproceedings{Karim_DESTINE_2024_ICRA,
    author = "Karim, Rezaul and Shabestary, Soheil Mohamad Alizadeh and Rasouli, Amir",
    booktitle = "ICRA",
    title = "DESTINE: Dynamic Goal Queries with Temporal Transductive Alignment for Trajectory Prediction",
    year = "2024"
}
        Chen et al., "CRITERIA: a New Benchmarking Paradigm for Evaluating Trajectory Prediction Models for Autonomous Driving", ICRA, 2024. paper arxiv code
          Datasets Metrics
          Bibtex 
          @inproceedings{Chen_CRITERIA_2024_ICRA,
    author = "Chen, Changhe and Pourkeshavarz, Mozhgan and Rasouli, Amir",
    booktitle = "ICRA",
    title = "CRITERIA: a New Benchmarking Paradigm for Evaluating Trajectory Prediction Models for Autonomous Driving",
    year = "2024"
}
        Afshar et al., "PBP: Path-based Trajectory Prediction for Autonomous Driving", ICRA, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @inproceedings{Afshar_PBP_2024_ICRA,
    author = "Afshar, Sepideh and Deo, Nachiket and Bhagat, Akshay and Chakraborty, Titas and Shao, Yunming and Buddharaju, Balarama Raju and Deshpande, Adwait and Motional, Henggang Cui",
    booktitle = "ICRA",
    title = "PBP: Path-based Trajectory Prediction for Autonomous Driving",
    year = "2024"
}
        Wang et al., "Improving Autonomous Driving Safety with POP: A Framework for Accurate Partially Observed Trajectory Predictions", ICRA, 2024. paper arxiv code
          Datasets Metrics
          Bibtex 
          @inproceedings{Wang_Improving_2024_ICRA,
    author = "Wang, Sheng and Chen, Yingbing and Cheng, Jie and Mei, Xiaodong and Xin, Ren and Song, Yongkang and Liu, Ming",
    booktitle = "ICRA",
    title = "Improving Autonomous Driving Safety with POP: A Framework for Accurate Partially Observed Trajectory Predictions",
    year = "2024"
}
        Woo et al., "FIMP: Future Interaction Modeling for Multi-Agent Motion Prediction", ICRA, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @inproceedings{Woo_FIMP_2024_ICRA,
    author = "Woo, Sungmin and Kim, Minjung and Kim, Donghyeong and Jang, Sungjun and Lee, Sangyoun",
    booktitle = "ICRA",
    title = "FIMP: Future Interaction Modeling for Multi-Agent Motion Prediction",
    year = "2024"
}
        Nivash et al., "SIMMF: Semantics-aware Interactive Multiagent Motion Forecasting for Autonomous Vehicle Driving", ICRA, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @inproceedings{Nivash_SIMMF_2024_ICRA,
    author = "Nivash, Vidyaa Krishnan and Qureshi, Ahmed H.",
    booktitle = "ICRA",
    title = "SIMMF: Semantics-aware Interactive Multiagent Motion Forecasting for Autonomous Vehicle Driving",
    year = "2024"
}
        Zhang et al., "SIMPL: A Simple and Efficient Multi-Agent Motion Prediction Baseline for Autonomous Driving", RAL, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @ARTICLE{Zhang_SIMPL_2024_RAL,
    author = "Zhang, Lu and Li, Peiliang and Liu, Sikang and Shen, Shaojie",
    journal = "RAL",
    title = "SIMPL: A Simple and Efficient Multi-Agent Motion Prediction Baseline for Autonomous Driving",
    year = "2024",
    volume = "9",
    number = "4",
    pages = "3767-3774"
}
        Rowe et al., "FJMP: Factorized Joint Multi-Agent Motion Prediction Over Learned Directed Acyclic Interaction Graphs", CVPR, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Rowe_2023_CVPR,
    author = "Rowe, Luke and Ethier, Martin and Dykhne, Eli-Henry and Czarnecki, Krzysztof",
    title = "FJMP: Factorized Joint Multi-Agent Motion Prediction Over Learned Directed Acyclic Interaction Graphs",
    booktitle = "CVPR",
    year = "2023"
}
        Zhou et al., "Query-Centric Trajectory Prediction", CVPR, 2023. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhou_2023_CVPR,
    author = "Zhou, Zikang and Wang, Jianping and Li, Yung-Hui and Huang, Yu-Kai",
    title = "Query-Centric Trajectory Prediction",
    booktitle = "CVPR",
    year = "2023"
}
        Zhu et al., "IPCC-TP: Utilizing Incremental Pearson Correlation Coefficient for Joint Multi-Agent Trajectory Prediction", CVPR, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhu_2023_CVPR,
    author = "Zhu, Dekai and Zhai, Guangyao and Di, Yan and Manhardt, Fabian and Berkemeyer, Hendrik and Tran, Tuan and Navab, Nassir and Tombari, Federico and Busam, Benjamin",
    title = "IPCC-TP: Utilizing Incremental Pearson Correlation Coefficient for Joint Multi-Agent Trajectory Prediction",
    booktitle = "CVPR",
    year = "2023"
}
        Wang et al., "ProphNet: Efficient Agent-Centric Motion Forecasting With Anchor-Informed Proposals", CVPR, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Wang_2023_CVPR_1,
    author = "Wang, Xishun and Su, Tong and Da, Fang and Yang, Xiaodong",
    title = "ProphNet: Efficient Agent-Centric Motion Forecasting With Anchor-Informed Proposals",
    booktitle = "CVPR",
    year = "2023"
}
        Aydemir et al., "ADAPT: Efficient Multi-Agent Trajectory Prediction with Adaptation", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Aydemir_2023_ICCV,
    author = "Aydemir, Gorkay and Akan, Adil Kaan and Guney, Fatma",
    title = "ADAPT: Efficient Multi-Agent Trajectory Prediction with Adaptation",
    booktitle = "ICCV",
    year = "2023"
}
        Chen et al., "Traj-MAE: Masked Autoencoders for Trajectory Prediction", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Chen_2023_ICCV,
    author = "Chen, Hao and Wang, Jiaze and Shao, Kun and Liu, Furui and Hao, Jianye and Guan, Chenyong and Chen, Guangyong and Heng, Pheng-Ann",
    title = "Traj-MAE: Masked Autoencoders for Trajectory Prediction",
    booktitle = "ICCV",
    year = "2023"
}
        Cheng et al., "Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoders", ICCV, 2023. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Cheng_2023_ICCV,
    author = "Cheng, Jie and Mei, Xiaodong and Liu, Ming",
    title = "Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoders",
    booktitle = "ICCV",
    year = "2023"
}
        Choi et al., "R-Pred: Two-Stage Motion Prediction Via Tube-Query Attention-Based Trajectory Refinement", ICCV, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Choi_2023_ICCV,
    author = "Choi, Sehwan and Kim, Jungho and Yun, Junyong and Choi, Jun Won",
    title = "R-Pred: Two-Stage Motion Prediction Via Tube-Query Attention-Based Trajectory Refinement",
    booktitle = "ICCV",
    year = "2023"
}
        Jiao et al., "Semi-supervised Semantics-guided Adversarial Training for Robust Trajectory Prediction", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Jiao_2023_ICCV,
    author = "Jiao, Ruochen and Liu, Xiangguo and Sato, Takami and Chen, Qi Alfred and Zhu, Qi",
    title = "Semi-supervised Semantics-guided Adversarial Training for Robust Trajectory Prediction",
    booktitle = "ICCV",
    year = "2023"
}
        Pourkeshavarz et al., "Learn TAROT with MENTOR: A Meta-Learned Self-Supervised Approach for Trajectory Prediction", ICCV, 2023. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Pourkeshavarz_2023_ICCV,
    author = "Pourkeshavarz, Mozhgan and Chen, Changhe and Rasouli, Amir",
    title = "Learn TAROT with MENTOR: A Meta-Learned Self-Supervised Approach for Trajectory Prediction",
    booktitle = "ICCV",
    year = "2023"
}
        Ye et al., "Bootstrap Motion Forecasting With Self-Consistent Constraints", ICCV, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Ye_2023_ICCV,
    author = "Ye, Maosheng and Xu, Jiamiao and Xu, Xunnong and Wang, Tengfei and Cao, Tongyi and Chen, Qifeng",
    title = "Bootstrap Motion Forecasting With Self-Consistent Constraints",
    booktitle = "ICCV",
    year = "2023"
}
        Cui et al., "GoRela: Go Relative for Viewpoint-Invariant Motion Forecasting", ICRA, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Cui_2023_ICRA,
    author = "Cui, Alexander and Casas, Sergio and Wong, Kelvin and Suo, Simon and Urtasun, Raquel",
    title = "GoRela: Go Relative for Viewpoint-Invariant Motion Forecasting",
    booktitle = "ICRA",
    year = "2023"
}
        Grimm et al., "Holistic Graph-based Motion Prediction", ICRA, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Grimm_2023_ICRA,
    author = "Grimm, Daniel and Schörner, Philip and Dreßler, Moritz and Zöllner, J.-Marius",
    title = "Holistic Graph-based Motion Prediction",
    booktitle = "ICRA",
    year = "2023"
}
        Nayakanti et al., "Wayformer: Motion Forecasting via Simple & Efficient Attention Networks", ICRA, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Nayakanti_2023_ICRA,
    author = "Nayakanti, Nigamaa and Al-Rfou, Rami and Zhou, Aurick and Goel, Kratarth and Refaat, Khaled S. and Sapp, Benjamin",
    title = "Wayformer: Motion Forecasting via Simple \& Efficient Attention Networks",
    booktitle = "ICRA",
    year = "2023"
}
        Schmidt et al., "Exploring Navigation Maps for Learning-Based Motion Prediction", ICRA, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Schmidt_2023_ICRA,
    author = "Schmidt, Julian and Jordan, Julian and Gritschneder, Franz and Monninger, Thomas and Dietmayer, Klaus",
    title = "Exploring Navigation Maps for Learning-Based Motion Prediction",
    booktitle = "ICRA",
    year = "2023"
}
        Ye et al., "Improving the Generalizability of Trajectory Prediction Models with Frenét-Based Domain Normalization", ICRA, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Ye_2023_ICRA,
    author = "Ye, Luyao and Zhou, Zikang and Wang, Jianping",
    title = "Improving the Generalizability of Trajectory Prediction Models with Frenét-Based Domain Normalization",
    booktitle = "ICRA",
    year = "2023"
}
        Feng et al., "MacFormer: Map-Agent Coupled Transformer for Real-Time and Robust Trajectory Prediction", RAL, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @ARTICLE{Feng_MacFormer_2023_RAL,
    author = "Feng, Chen and Zhou, Hangning and Lin, Huadong and Zhang, Zhigang and Xu, Ziyao and Zhang, Chi and Zhou, Boyu and Shen, Shaojie",
    journal = "RAL",
    title = "MacFormer: Map-Agent Coupled Transformer for Real-Time and Robust Trajectory Prediction",
    year = "2023",
    volume = "8",
    number = "10",
    pages = "6795-6802"
}
        Gao et al., "Dynamic Scenario Representation Learning for Motion Forecasting With Heterogeneous Graph Convolutional Recurrent Networks", RAL, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @ARTICLE{Gao_Dynamic_2023_RAL,
    author = "Gao, Xing and Jia, Xiaogang and Li, Yikang and Xiong, Hongkai",
    journal = "RAL",
    title = "Dynamic Scenario Representation Learning for Motion Forecasting With Heterogeneous Graph Convolutional Recurrent Networks",
    year = "2023",
    volume = "8",
    number = "5",
    pages = "2946-2953"
}
        Kim et al., "Diverse Multiple Trajectory Prediction Using a Two-Stage Prediction Network Trained With Lane Loss", RAL, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @ARTICLE{Kim_Diverse_2023_RAL,
    author = "Kim, Sanmin and Jeon, Hyeongseok and Choi, Jun Won and Kum, Dongsuk",
    journal = "RAL",
    title = "Diverse Multiple Trajectory Prediction Using a Two-Stage Prediction Network Trained With Lane Loss",
    year = "2023",
    volume = "8",
    number = "4",
    pages = "2038-2045"
}
        Mo et al., "Map-Adaptive Multimodal Trajectory Prediction Using Hierarchical Graph Neural Networks", RAL, 2023. paper
          Datasets Metrics
          Bibtex 
          @ARTICLE{Mo_Map_2023_RAL,
    author = "Mo, Xiaoyu and Xing, Yang and Liu, Haochen and Lv, Chen",
    journal = "RAL",
    title = "Map-Adaptive Multimodal Trajectory Prediction Using Hierarchical Graph Neural Networks",
    year = "2023",
    volume = "8",
    number = "6",
    pages = "3685-3692"
}
        Wang et al., "GANet: Goal Area Network for Motion Forecasting", ICRA, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Wang_2023_ICRA_1,
    author = "Wang, Mingkun and Zhu, Xinge and Yu, Changqian and Li, Wei and Ma, Yuexin and Jin, Ruochun and Ren, Xiaoguang and Ren, Dongchun and Wang, Mingxu and Yang, Wenjing",
    title = "GANet: Goal Area Network for Motion Forecasting",
    booktitle = "ICRA",
    year = "2023"
}
        Fan et al., "Look Before You Drive: Boosting Trajectory Forecasting via Imagining Future", IROS, 2023. paper
          Datasets Metrics
          Bibtex 
          @INPROCEEDINGS{Fan_2023_IROS,
    author = "Fan, Yixuan and Liu, Xin and Li, Yali and Wang, Shengjin",
    booktitle = "IROS",
    title = "Look Before You Drive: Boosting Trajectory Forecasting via Imagining Future",
    year = "2023"
}
        Bahari et al., "Vehicle Trajectory Prediction Works, but Not Everywhere", CVPR, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Bahari_2022_CVPR,
    author = "Bahari, Mohammadhossein and Saadatnejad, Saeed and Rahimi, Ahmad and Shaverdikondori, Mohammad and Shahidzadeh, Amir Hossein and Moosavi-Dezfooli, Seyed-Mohsen and Alahi, Alexandre",
    title = "Vehicle Trajectory Prediction Works, but Not Everywhere",
    booktitle = "CVPR",
    year = "2022"
}
        Zhou et al., "HiVT: Hierarchical Vector Transformer for Multi-Agent Motion Prediction", CVPR, 2022. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhou_2022_CVPR,
    author = "Zhou, Zikang and Ye, Luyao and Wang, Jianping and Wu, Kui and Lu, Kejie",
    title = "{HiVT}: Hierarchical Vector Transformer for Multi-Agent Motion Prediction",
    booktitle = "CVPR",
    year = "2022"
}
        Wang et al., "LTP: Lane-Based Trajectory Prediction for Autonomous Driving", CVPR, 2022. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Wang_2022_CVPR_3,
    author = "Wang, Jingke and Ye, Tengju and Gu, Ziqing and Chen, Junbo",
    title = "{LTP}: Lane-Based Trajectory Prediction for Autonomous Driving",
    booktitle = "CVPR",
    year = "2022"
}
        Choi et al., "Hierarchical Latent Structure for Multi-modal Vehicle Trajectory Forecasting", ECCV, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Choi_2022_ECCV,
    author = "Choi, Dooseop and Min, KyoungWook",
    title = "Hierarchical Latent Structure for Multi-modal Vehicle Trajectory Forecasting",
    booktitle = "ECCV",
    year = "2022"
}
        Zhong et al., "Aware of the History: Trajectory Forecasting with the Local Behavior Data", ECCV, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhong_2022_ECCV,
    author = "Zhong, Yiqi and Ni, Zhenyang and Chen, Siheng and Neumann, Ulrich",
    title = "Aware of the History: Trajectory Forecasting with the Local Behavior Data",
    booktitle = "ECCV",
    year = "2022"
}
        Bhattacharyya et al., "SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Driving", CoRL, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Bhattacharyya_2022_CoRL,
    author = "Bhattacharyya, Prarthana and Huang, Chengjie and Czarnecki, Krzysztof",
    title = "{SSL}-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous Driving",
    booktitle = "CoRL",
    year = "2022"
}
        Girgis et al., "Latent Variable Sequential Set Transformers for Joint Multi-Agent Motion Prediction", ICLR, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Girgis_2022_ICLR,
    author = "Girgis, Roger and Golemo, Florian and Codevilla, Felipe and Weiss, Martin and D'Souza, Jim Aldon and Kahou, Samira Ebrahimi and Heide, Felix and Pal, Christopher",
    title = "Latent Variable Sequential Set Transformers for Joint Multi-Agent Motion Prediction",
    booktitle = "ICLR",
    year = "2022"
}
        Ngiam et al., "Scene Transformer: A Unified Architecture for Predicting Future Trajectories of Multiple Agents", ICLR, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Ngiam_2022_ICLR,
    author = "Ngiam, Jiquan and Vasudevan, Vijay and Caine, Benjamin and Zhang, Zhengdong and Chiang, Hao-Tien Lewis and Ling, Jeffrey and Roelofs, Rebecca and Bewley, Alex and Liu, Chenxi and Venugopal, Ashish and Weiss, David J and Sapp, Ben and Chen, Zhifeng and Shlens, Jonathon",
    title = "{Scene Transformer}: A Unified Architecture for Predicting Future Trajectories of Multiple Agents",
    booktitle = "ICLR",
    year = "2022"
}
        Da et al., "Path-Aware Graph Attention for HD Maps in Motion Prediction", ICRA, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Da_2022_ICRA,
    author = "Da, Fang and Zhang, Yu",
    booktitle = "ICRA",
    title = "Path-Aware Graph Attention for HD Maps in Motion Prediction",
    year = "2022"
}
        Gilles et al., "GOHOME: Graph-Oriented Heatmap Output for future Motion Estimation", ICRA, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Gilles_2022_ICRA,
    author = "Gilles, Thomas and Sabatini, Stefano and Tsishkou, Dzmitry and Stanciulescu, Bogdan and Moutarde, Fabien",
    booktitle = "ICRA",
    title = "{GOHOME}: Graph-Oriented Heatmap Output for future Motion Estimation",
    year = "2022"
}
        Huang et al., "Multi-modal Motion Prediction with Transformer-based Neural Network for Autonomous Driving", ICRA, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Huang_2022_ICRA,
    author = "Huang, Zhiyu and Mo, Xiaoyu and Lv, Chen",
    booktitle = "ICRA",
    title = "Multi-modal Motion Prediction with Transformer-based Neural Network for Autonomous Driving",
    year = "2022"
}
        Kim et al., "StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving", ICRA, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Kim_2022_ICRA,
    author = "Kim, Jinkyu and Mahjourian, Reza and Ettinger, Scott and Bansal, Mayank and White, Brandyn and Sapp, Ben and Anguelov, Dragomir",
    booktitle = "ICRA",
    title = "{StopNet}: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving",
    year = "2022"
}
        Kuo et al., "Trajectory Prediction with Linguistic Representations", ICRA, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Kuo_2022_ICRA,
    author = "Kuo, Yen-Ling and Huang, Xin and Barbu, Andrei and McGill, Stephen G. and Katz, Boris and Leonard, John J. and Rosman, Guy",
    booktitle = "ICRA",
    title = "Trajectory Prediction with Linguistic Representations",
    year = "2022"
}
        Schmidt et al., "CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attention", ICRA, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Schmidt_2022_ICRA,
    author = "Schmidt, Julian and Jordan, Julian and Gritschneder, Franz and Dietmayer, Klaus",
    booktitle = "ICRA",
    title = "{CRAT-Pred}: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attention",
    year = "2022"
}
        Su et al., "Narrowing the Coordinate-frame Gap in Behavior Prediction Models: Distillation for Efficient and Accurate Scene-centric Motion Forecasting", ICRA, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Su_2022_ICRA,
    author = "Su, DiJia Andy and Douillard, Bertrand and Al-Rfou, Rami and Park, Cheol and Sapp, Benjamin",
    booktitle = "ICRA",
    title = "Narrowing the Coordinate-frame Gap in Behavior Prediction Models: Distillation for Efficient and Accurate Scene-centric Motion Forecasting",
    year = "2022"
}
        Strohbeck et al., "Deep Kernel Learning for Uncertainty Estimation in Multiple Trajectory Prediction Networks", IROS, 2022. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Strohbeck_2022_IROS,
    author = "Strohbeck, Jan and Muller, Johannes and Herrmann, Martin and Buchholz, Michael",
    booktitle = "IROS",
    title = "Deep Kernel Learning for Uncertainty Estimation in Multiple Trajectory Prediction Networks",
    year = "2022"
}
        Zhang et al., "Trajectory Prediction with Graph-based Dual-scale Context Fusion", IROS, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhang_2022_IROS,
    author = "Zhang, Lu and Li, Peiliang and Chen, Jing and Shen, Shaojie",
    booktitle = "IROS",
    title = "Trajectory Prediction with Graph-based Dual-scale Context Fusion",
    year = "2022"
}
        Tang et al., "Collaborative Uncertainty in Multi-Agent Trajectory Forecasting", NeurIPS, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Tang_2021_NeurIPS,
    author = "Tang, Bohan and Zhong, Yiqi and Neumann, Ulrich and Wang, Gang and Chen, Siheng and Zhang, Ya",
    booktitle = "NeurIPS",
    title = "Collaborative Uncertainty in Multi-Agent Trajectory Forecasting",
    year = "2021"
}
        Walters et al., "Trajectory Prediction using Equivariant Continuous Convolution", ICLR, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Walters_2021_ICLR,
    author = "Walters, Robin and Li, Jinxi and Yu, Rose",
    booktitle = "ICLR",
    title = "Trajectory Prediction using Equivariant Continuous Convolution",
    year = "2021"
}
        Amirloo et al., "Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map", CVPR, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Amirloo_2021_CVPR,
    author = "Amirloo, Elmira and Rohani, Mohsen and Banijamali, Ershad and Luo, Jun and Poupart, Pascal",
    title = "Self-Supervised Simultaneous Multi-Step Prediction of Road Dynamics and Cost Map",
    booktitle = "CVPR",
    year = "2021"
}
        Kim et al., "LaPred: Lane-Aware Prediction of Multi-Modal Future Trajectories of Dynamic Agents", CVPR, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Kim_2021_CVPR,
    author = "Kim, ByeoungDo and Park, Seong Hyeon and Lee, Seokhwan and Khoshimjonov, Elbek and Kum, Dongsuk and Kim, Junsoo and Kim, Jeong Soo and Choi, Jun Won",
    title = "{LaPred}: Lane-Aware Prediction of Multi-Modal Future Trajectories of Dynamic Agents",
    booktitle = "CVPR",
    year = "2021"
}
        Liu et al., "Multimodal Motion Prediction With Stacked Transformers", CVPR, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Liu_2021_CVPR,
    author = "Liu, Yicheng and Zhang, Jinghuai and Fang, Liangji and Jiang, Qinhong and Zhou, Bolei",
    title = "Multimodal Motion Prediction With Stacked Transformers",
    booktitle = "CVPR",
    year = "2021"
}
        Ye et al., "TPCN: Temporal Point Cloud Networks for Motion Forecasting", CVPR, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Ye_2021_CVPR,
    author = "Ye, Maosheng and Cao, Tongyi and Chen, Qifeng",
    title = "{TPCN}: Temporal Point Cloud Networks for Motion Forecasting",
    booktitle = "CVPR",
    year = "2021"
}
        Banijamali et al., "Prediction by Anticipation: An Action-Conditional Prediction Method Based on Interaction Learning", ICCV, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Banijamali_2021_ICCV,
    author = "Banijamali, Ershad and Rohani, Mohsen and Amirloo, Elmira and Luo, Jun and Poupart, Pascal",
    title = "Prediction by Anticipation: An Action-Conditional Prediction Method Based on Interaction Learning",
    booktitle = "ICCV",
    year = "2021"
}
        Gu et al., "DenseTNT: End-to-End Trajectory Prediction From Dense Goal Sets", ICCV, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Gu_2021_ICCV,
    author = "Gu, Junru and Sun, Chen and Zhao, Hang",
    title = "{DenseTNT}: End-to-End Trajectory Prediction From Dense Goal Sets",
    booktitle = "ICCV",
    year = "2021"
}
        Zheng et al., "Unlimited Neighborhood Interaction for Heterogeneous Trajectory Prediction", ICCV, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zheng_2021_ICCV,
    author = "Zheng, Fang and Wang, Le and Zhou, Sanping and Tang, Wei and Niu, Zhenxing and Zheng, Nanning and Hua, Gang",
    title = "Unlimited Neighborhood Interaction for Heterogeneous Trajectory Prediction",
    booktitle = "ICCV",
    year = "2021"
}
        Tolstaya et al., "Identifying Driver Interactions via Conditional Behavior Prediction", ICRA, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Tolstaya_2021_ICRA,
    author = "Tolstaya, Ekaterina and Mahjourian, Reza and Downey, Carlton and Vadarajan, Balakrishnan and Sapp, Benjamin and Anguelov, Dragomir",
    booktitle = "ICRA",
    title = "Identifying Driver Interactions via Conditional Behavior Prediction",
    year = "2021"
}
        Zhu et al., "Star Topology based Interaction for Robust Trajectory Forecasting in Dynamic Scene", ICRA, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhu_2021_ICRA,
    author = "Zhu, Yanliang and Ren, Dongchun and Qian, Deheng and Fan, Mingyu and Li, Xin and Xia, Huaxia",
    booktitle = "ICRA",
    title = "Star Topology based Interaction for Robust Trajectory Forecasting in Dynamic Scene",
    year = "2021"
}
        Wang et al., "Multiple Contextual Cues Integrated Trajectory Prediction for Autonomous Driving", RAL, 2021. paper
          Datasets Metrics
          Bibtex 
          @Article{Wang_2021_RAL,
    author = "Wang, Li and Wu, Tao and Fu, Hao and Xiao, Liang and Wang, Zhiyu and Dai, Bin",
    journal = "RAL",
    title = "Multiple Contextual Cues Integrated Trajectory Prediction for Autonomous Driving",
    year = "2021",
    volume = "6",
    number = "4",
    pages = "6844-6851"
}
        Rella et al., "Decoder Fusion RNN: Context and Interaction Aware Decoders for Trajectory Prediction", IROS, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Rella_2021_IROS,
    author = "Rella, Edoardo Mello and Zaech, Jan-Nico and Liniger, Alexander and Van Gool, Luc",
    booktitle = "IROS",
    title = "Decoder {Fusion RNN}: Context and Interaction Aware Decoders for Trajectory Prediction",
    year = "2021"
}
        Zeng et al., "LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting", IROS, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zeng_2021_IROS,
    author = "Zeng, Wenyuan and Liang, Ming and Liao, Renjie and Urtasun, Raquel",
    booktitle = "IROS",
    title = "{LaneRCNN}: Distributed Representations for Graph-Centric Motion Forecasting",
    year = "2021"
}
        Song et al., "Learning to Predict Vehicle Trajectories with Model-based Planning", CoRL, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Song_2021_CoRL,
    author = "Song, Haoran and Luan, Di and Ding, Wenchao and Wang, Michael Y and Chen, Qifeng",
    title = "Learning to Predict Vehicle Trajectories with Model-based Planning",
    booktitle = "CoRL",
    year = "2021"
}
        Zhu et al., "Motion Forecasting with Unlikelihood Training in Continuous Space", CoRL, 2021. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhu_2021_CoRL,
    author = "Zhu, Deyao and Zahran, Mohamed and Li, Li Erran and Elhoseiny, Mohamed",
    title = "Motion Forecasting with Unlikelihood Training in Continuous Space",
    booktitle = "CoRL",
    year = "2021"
}
        Fang et al., "TPNet: Trajectory Proposal Network for Motion Prediction", CVPR, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Fang_2020_CVPR,
    author = "Fang, Liangji and Jiang, Qinhong and Shi, Jianping and Zhou, Bolei",
    title = "{TPNet}: Trajectory Proposal Network for Motion Prediction",
    booktitle = "CVPR",
    year = "2020"
}
        Gao et al., "VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation", CVPR, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Gao_2020_CVPR,
    author = "Gao, Jiyang and Sun, Chen and Zhao, Hang and Shen, Yi and Anguelov, Dragomir and Li, Congcong and Schmid, Cordelia",
    title = "VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation",
    booktitle = "CVPR",
    year = "2020"
}
        Liang et al., "Learning Lane Graph Representations for Motion Forecasting", ECCV, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Liang_2020_ECCV_2,
    author = "Liang, Ming and Yang, Bin and Hu, Rui and Chen, Yun and Liao, Renjie and Feng, Song and Urtasun, Raquel",
    title = "Learning Lane Graph Representations for Motion Forecasting",
    booktitle = "ECCV",
    year = "2020"
}
        Liu et al., "SMART: Simultaneous Multi-Agent Recurrent Trajectory Prediction", ECCV, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Liu_2020_ECCV_2,
    author = "Liu, Buyu and Pittaluga, Francesco and Chandraker, Manmohan and others",
    title = "{SMART}: Simultaneous Multi-Agent Recurrent Trajectory Prediction",
    booktitle = "ECCV",
    year = "2020"
}
        Liang et al., "SimAug: Learning Robust Representations from Simulation for Trajectory Prediction", ECCV, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Liang_2020_ECCV,
    author = "Liang, Junwei and Jiang, Lu and Hauptmann, Alexander",
    title = "{SimAug}: Learning Robust Representations from Simulation for Trajectory Prediction",
    booktitle = "ECCV",
    year = "2020"
}
        Park et al., "Diverse and Admissible Trajectory Forecasting through Multimodal Context Understanding", ECCV, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Park_2020_ECCV,
    author = "Park, Seong Hyeon and Lee, Gyubok and Bhat, Manoj and Seo, Jimin and Kang, Minseok and Francis, Jonathan and Jadhav, Ashwin R and Liang, Paul Pu and Morency, Louis-Philippe",
    title = "Diverse and Admissible Trajectory Forecasting through Multimodal Context Understanding",
    booktitle = "ECCV",
    year = "2020"
}
        Biktairov et al., "PRANK: Motion Prediction Based on RANKing", NeurIPS, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Biktairov_2020_NeurIPS,
    author = "Biktairov, Yuriy and Stebelev, Maxim and Rudenko, Irina and Shliazhko, Oleh and Yangel, Boris",
    booktitle = "NeurIPS",
    title = "{PRANK}: Motion Prediction Based on {RANKing}",
    year = "2020"
}
        Kawasaki et al., "Multimodal Trajectory Predictions for Urban Environments Using Geometric Relationships between a Vehicle and Lanes", ICRA, 2020. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Kawasaki_2020_ICRA,
    author = "Kawasaki, A. and Seki, A.",
    booktitle = "ICRA",
    title = "Multimodal Trajectory Predictions for Urban Environments Using Geometric Relationships between a Vehicle and Lanes",
    year = "2020"
}
        He et al., "UST: Unifying Spatio-Temporal Context for Trajectory Prediction in Autonomous Driving", IROS, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{He_2020_IROS,
    author = "He, H. and Dai, H. and Wang, N.",
    booktitle = "IROS",
    title = "UST: Unifying Spatio-Temporal Context for Trajectory Prediction in Autonomous Driving",
    year = "2020"
}
        Luo et al., "Probabilistic Multi-modal Trajectory Prediction with Lane Attention for Autonomous Vehicles", IROS, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Luo_2020_IROS,
    author = "Luo, C. and Sun, L. and Dabiri, D. and Yuille, A.",
    booktitle = "IROS",
    title = "Probabilistic Multi-modal Trajectory Prediction with Lane Attention for Autonomous Vehicles",
    year = "2020"
}
        Strohbeck et al., "Multiple Trajectory Prediction with Deep Temporal and Spatial Convolutional Neural Networks", IROS, 2020. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Strohbeck_2020_IROS,
    author = "Strohbeck, J. and Belagiannis, V. and Müller, J. and Schreiber, M. and Herrmann, M. and Wolf, D. and Buchholz, M.",
    booktitle = "IROS",
    title = "Multiple Trajectory Prediction with Deep Temporal and Spatial Convolutional Neural Networks",
    year = "2020"
}
        Chandra et al., "Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs", RAL, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @Article{Chandra_2020_RAL,
    author = "Chandra, R. and Guan, T. and Panuganti, S. and Mittal, T. and Bhattacharya, U. and Bera, A. and Manocha, D.",
    journal = "RAL",
    title = "Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in {Graph-LSTMs}",
    year = "2020",
    volume = "5",
    number = "3",
    pages = "4882-4890"
}
        Huang et al., "DiversityGAN: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling", RAL, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @Article{Huang_2020_RAL,
    author = "Huang, X. and McGill, S. G. and DeCastro, J. A. and Fletcher, L. and Leonard, J. J. and Williams, B. C. and Rosman, G.",
    journal = "RAL",
    title = "{DiversityGAN}: Diversity-Aware Vehicle Motion Prediction via Latent Semantic Sampling",
    year = "2020",
    volume = "5",
    number = "4",
    pages = "5089-5096"
}
        Zhao et al., "TNT: Target-driven Trajectory Prediction", CoRL, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhao_2020_CORL,
    author = "Zhao, Hang and Gao, Jiyang and Lan, Tian and Sun, Chen and Sapp, Benjamin and Varadarajan, Balakrishnan and Shen, Yue and Shen, Yi and Chai, Yuning and Schmid, Cordelia and others",
    title = "{TNT}: Target-driven Trajectory Prediction",
    booktitle = "CoRL",
    year = "2020"
}
        Chang et al., "Argoverse: 3D Tracking And Forecasting With Rich Maps", CVPR, 2019. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Chang_2019_CVPR,
    author = "Chang, Ming-Fang and Lambert, John and Sangkloy, Patsorn and Singh, Jagjeet and Bak, Slawomir and Hartnett, Andrew and Wang, De and Carr, Peter and Lucey, Simon and Ramanan, Deva and Hays, James",
    title = "Argoverse: {3D} Tracking And Forecasting With Rich Maps",
    booktitle = "CVPR",
    year = "2019"
}
        Tang et al., "Multiple futures prediction", NeurIPS, 2019. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Tang_2019_NeurIPS,
    author = "Tang, Charlie and Salakhutdinov, Russ R",
    title = "Multiple futures prediction",
    booktitle = "NeurIPS",
    year = "2019"
}
        Agro et al., "UnO: Unsupervised Occupancy Fields for Perception and Forecasting", CVPR, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Agro_UnO_2024_CVPR,
    author = "Agro, Ben and Sykora, Quinlan and Casas, Sergio and Gilles, Thomas and Urtasun, Raquel",
    title = "UnO: Unsupervised Occupancy Fields for Perception and Forecasting",
    booktitle = "CVPR",
    year = "2024"
}
        Agro et al., "Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving", CVPR, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Agro_2023_CVPR,
    author = "Agro, Ben and Sykora, Quinlan and Casas, Sergio and Urtasun, Raquel",
    title = "Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving",
    booktitle = "CVPR",
    year = "2023"
}
        Khurana et al., "Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting", CVPR, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Khurana_2023_CVPR,
    author = "Khurana, Tarasha and Hu, Peiyun and Held, David and Ramanan, Deva",
    title = "Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting",
    booktitle = "CVPR",
    year = "2023"
}
      Bibtex 
      @InProceedings{Chang_2019_CVPR,
    author = "Chang, Ming-Fang and Lambert, John and Sangkloy, Patsorn and Singh, Jagjeet and Bak, Slawomir and Hartnett, Andrew and Wang, De and Carr, Peter and Lucey, Simon and Ramanan, Deva and Hays, James",
    title = "Argoverse: {3D} Tracking And Forecasting With Rich Maps",
    booktitle = "CVPR",
    year = "2019"
}
    Argoverse Streaming motion Forecasting (Argoverse-SF) link paper arxiv
    • Summary: A dataset of driving scenarios based on Argoverse designed for streaming motion forecasting problem.
    • Applications: Trajectory prediction
    • Data type and annotations: RGB, LIDAR, 3D bounding box, Map, Trajectory
    • Task: Driving
      Used in papers
        Pang et al., "Streaming Motion Forecasting for Autonomous Driving", IROS, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @INPROCEEDINGS{Pang_2023_IROS,
    author = "Pang, Ziqi and Ramanan, Deva and Li, Mengtian and Wang, Yu-Xiong",
    booktitle = "IROS",
    title = "Streaming Motion Forecasting for Autonomous Driving",
    year = "2023"
}
      Bibtex 
      @INPROCEEDINGS{Pang_2023_IROS,
    author = "Pang, Ziqi and Ramanan, Deva and Li, Mengtian and Wang, Yu-Xiong",
    booktitle = "IROS",
    title = "Streaming Motion Forecasting for Autonomous Driving",
    year = "2023"
}
    ATC link paper
    • Summary: A dataset of human tracks recorded in a shopping mall for a period of 92 days using 3D range sensors
    • Applications: Trajectory prediction
    • Data type and annotations: RGB, trajectory, attribute, depth
    • Task: Surveillance
      Used in papers
        Zhu et al., "LaCE-LHMP: Airflow Modelling-Inspired Long-Term Human Motion Prediction By Enhancing Laminar Characteristics in Human Flow", ICRA, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @inproceedings{Zhu_LaCE_2024_ICRA,
    author = "Zhu, Yufei and Fan, Han and Rudenko, Andrey and Magnusson, Martin and Schaffernicht, Erik and Lilienthal, Achim J.",
    booktitle = "ICRA",
    title = "LaCE-LHMP: Airflow Modelling-Inspired Long-Term Human Motion Prediction By Enhancing Laminar Characteristics in Human Flow",
    year = "2024"
}
        Wakulicz et al., "Topological Trajectory Prediction with Homotopy Classes", ICRA, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Wakulicz_2023_ICRA,
    author = "Wakulicz, Jennifer and Brian Lee, Ki Myung and Vidal-Calleja, Teresa and Fitch, Robert",
    title = "Topological Trajectory Prediction with Homotopy Classes",
    booktitle = "ICRA",
    year = "2023"
}
        Kiss et al., "Constrained Gaussian Processes With Integrated Kernels for Long-Horizon Prediction of Dense Pedestrian Crowd Flows", RAL, 2022. paper
          Datasets Metrics
          Bibtex 
          @Article{Kiss_2023_RAL,
    author = "Kiss, Stefan H. and Katuwandeniya, Kavindie and Alempijevic, Alen and Vidal-Calleja, Teresa",
    journal = "RAL",
    title = "Constrained Gaussian Processes With Integrated Kernels for Long-Horizon Prediction of Dense Pedestrian Crowd Flows",
    year = "2022",
    volume = "7",
    number = "3",
    pages = "7343-7350"
}
        Zhu et al., "CLiFF-LHMP: Using Spatial Dynamics Patterns for Long- Term Human Motion Prediction", IROS, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @INPROCEEDINGS{Zhu_2023_IROS,
    author = "Zhu, Yufei and Rudenko, Andrey and Kucner, Tomasz P. and Palmieri, Luigi and Arras, Kai O. and Lilienthal, Achim J. and Magnusson, Martin",
    booktitle = "IROS",
    title = "CLiFF-LHMP: Using Spatial Dynamics Patterns for Long- Term Human Motion Prediction",
    year = "2023"
}
        Rudenko et al., "Joint Long-Term Prediction Of Human Motion Using A Planning-Based Social Force Approach", ICRA, 2018. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Rudenko_2018_ICRA,
    author = "Rudenko, A. and Palmieri, L. and Arras, K. O.",
    booktitle = "ICRA",
    title = "Joint Long-Term Prediction Of Human Motion Using A Planning-Based Social Force Approach",
    year = "2018"
}
      Bibtex 
      @Article{Brvsvcic_2013_HMS,
    author = "Br\vs\vci\'c, Dra{\v{z}}en and Kanda, Takayuki and Ikeda, Tetsushi and Miyashita, Takahiro",
    title = "Person Tracking In Large Public Spaces Using 3-D Range Sensors",
    journal = "Transactions on Human-Machine Systems",
    volume = "43",
    number = "6",
    pages = "522--534",
    year = "2013"
}
    Atomic Visual Actions (AVA) link paper arxiv
    • Summary: An action dataset of 80 atomic visual actions in 430 videos with 1.62M corresponding labels localized in space and time
    • Applications: Action prediction
    • Data type and annotations: RGB, activity label, temporal segment
    • Task: Activity
      Used in papers
        Sun et al., "Relational Action Forecasting", CVPR, 2019. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Sun_2019_CVPR,
    author = "Sun, Chen and Shrivastava, Abhinav and Vondrick, Carl and Sukthankar, Rahul and Murphy, Kevin and Schmid, Cordelia",
    title = "Relational Action Forecasting",
    booktitle = "CVPR",
    year = "2019"
}
      Bibtex 
      @InProceedings{Gu_2018_CVPR,
    author = "Gu, Chunhui and Sun, Chen and Ross, David A and Vondrick, Carl and Pantofaru, Caroline and Li, Yeqing and Vijayanarasimhan, Sudheendra and Toderici, George and Ricco, Susanna and Sukthankar, Rahul and others",
    title = "{AVA}: A Video Dataset Of Spatio-Temporally Localized Atomic Visual Actions",
    booktitle = "CVPR",
    year = "2018"
}
    Audi Autonomous Driving Dataset (A2D2) link arxiv
    • Summary: A dataset of 40k frames of driving with semantic segmentation, 12k frames with 3D bounding boxes and 390k unlabelled footage collected in 3 cities.
    • Applications: Trajectory prediction
    • Data type and annotations: RGB, LIDAR, 3D Bounding Box, Semantic Segment
    • Task: Driving
      Used in papers
        Buhet et al., "PLOP: Probabilistic PoLynomial Objects Trajectory Planning for Autonomous Driving", CoRL, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Buhet_2020_CORL,
    author = "Buhet, Thibault and Wirbel, Emilie and Bursuc, Andrei and Perrotton, Xavier",
    title = "{PLOP}: Probabilistic PoLynomial Objects Trajectory Planning for Autonomous Driving",
    booktitle = "CoRL",
    year = "2020"
}
      Bibtex 
      @Article{Geyer_2020_arxiv,
    author = {Geyer, Jakob and Kassahun, Yohannes and Mahmudi, Mentar and Ricou, Xavier and Durgesh, Rupesh and Chung, Andrew S and Hauswald, Lorenz and Pham, Viet Hoang and M{\"u}hlegg, Maximilian and Dorn, Sebastian and others},
    title = "{A2d2}: Audi Autonomous Driving Dataset",
    journal = "arXiv:2004.06320",
    year = "2020"
}
    BABEL link arxiv
    • Summary: A dataset with language labels describing the actions being performed in mocap sequences for about 43 hour.
    • Applications: Motion prediction
    • Data type and annotations: 3D Pose, Activity Label, Text
    • Task: Action
      Used in papers
        Sun et al., "DeFeeNet: Consecutive 3D Human Motion Prediction With Deviation Feedback", CVPR, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Sun_2023_CVPR,
    author = "Sun, Xiaoning and Sun, Huaijiang and Li, Bin and Wei, Dong and Li, Weiqing and Lu, Jianfeng",
    title = "DeFeeNet: Consecutive 3D Human Motion Prediction With Deviation Feedback",
    booktitle = "CVPR",
    year = "2023"
}
        Mao et al., "Weakly-Supervised Action Transition Learning for Stochastic Human Motion Prediction", CVPR, 2022. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Mao_2022_CVPR,
    author = "Mao, Wei and Liu, Miaomiao and Salzmann, Mathieu",
    title = "Weakly-Supervised Action Transition Learning for Stochastic Human Motion Prediction",
    booktitle = "CVPR",
    year = "2022"
}
        Nawhal et al., "Rethinking Learning Approaches for Long-Term Action Anticipation", ECCV, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Nawhal_2022_ECCV,
    author = "Nawhal, Megha and Jyothi, Akash Abdu and Mori, Greg",
    title = "Rethinking Learning Approaches for Long-Term Action Anticipation",
    booktitle = "ECCV",
    year = "2022"
}
      Bibtex 
      @InProceedings{Punnakkal_2021_CVPR,
    author = "Punnakkal, Abhinanda R. and Chandrasekaran, Arjun and Athanasiou, Nikos and Quiros-Ramirez, Alejandra and Black, Michael J.",
    title = "{BABEL}: Bodies, Action and Behavior With English Labels",
    booktitle = "CVPR",
    year = "2021"
}
    BAIR Push link paper arxiv
    • Summary: A dataset of object manipulation using a robot arm with 59k object pushing motion samples
    • Applications: Video prediction
    • Data type and annotations: RGB
    • Task: Robot object manipulation
      Used in papers
        Shrivastava et al., "Video Prediction by Modeling Videos as Continuous Multi-Dimensional Processes", CVPR, 2024. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Shrivastava_Video_2024_CVPR,
    author = "Shrivastava, Gaurav and Shrivastava, Abhinav",
    title = "Video Prediction by Modeling Videos as Continuous Multi-Dimensional Processes",
    booktitle = "CVPR",
    year = "2024"
}
        Zhang et al., "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction", CVPR, 2024. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhang_ExtDM_2024_CVPR,
    author = "Zhang, Zhicheng and Hu, Junyao and Cheng, Wentao and Paudel, Danda and Yang, Jufeng",
    title = "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction",
    booktitle = "CVPR",
    year = "2024"
}
        Davtyan et al., "Efficient Video Prediction via Sparsely Conditioned Flow Matching", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Davtyan_2023_ICCV,
    author = "Davtyan, Aram and Sameni, Sepehr and Favaro, Paolo",
    title = "Efficient Video Prediction via Sparsely Conditioned Flow Matching",
    booktitle = "ICCV",
    year = "2023"
}
        Chatterjee et al., "A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction", ICCV, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Chatterjee_2021_ICCV,
    author = "Chatterjee, Moitreya and Ahuja, Narendra and Cherian, Anoop",
    title = "A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction",
    booktitle = "ICCV",
    year = "2021"
}
        Jin et al., "Exploring Spatial-Temporal Multi-Frequency Analysis for High-Fidelity and Temporal-Consistency Video Prediction", CVPR, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Jin_2020_CVPR,
    author = "Jin, Beibei and Hu, Yu and Tang, Qiankun and Niu, Jingyu and Shi, Zhiping and Han, Yinhe and Li, Xiaowei",
    title = "Exploring Spatial-Temporal Multi-Frequency Analysis for High-Fidelity and Temporal-Consistency Video Prediction",
    booktitle = "CVPR",
    year = "2020"
}
        Franceschi et al., "Stochastic Latent Residual Video Prediction", ICML, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Franceschi_2020_ICML,
    author = {Franceschi, Jean-Yves and Delasalles, Edouard and Chen, Micka{\"e}l and Lamprier, Sylvain and Gallinari, Patrick},
    title = "Stochastic Latent Residual Video Prediction",
    booktitle = "ICML",
    year = "2020"
}
        Xu et al., "Video Prediction via Example Guidance", ICML, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Xu_2020_ICML,
    author = "Xu, Jingwei and Xu, Huazhe and Ni, Bingbing and Yang, Xiaokang and Darrell, Trevor",
    title = "Video Prediction via Example Guidance",
    booktitle = "ICML",
    year = "2020"
}
        Castrejon et al., "Improved Conditional VRNNs For Video Prediction", ICCV, 2019. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Castrejon_2019_ICCV,
    author = "Castrejon, Lluis and Ballas, Nicolas and Courville, Aaron",
    title = "Improved Conditional {VRNNs} For Video Prediction",
    booktitle = "ICCV",
    year = "2019"
}
        Xu et al., "Video Prediction Via Selective Sampling", NeurIPS, 2018. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Xu_2018_NeurIPS,
    author = "Xu, Jingwei and Ni, Bingbing and Yang, Xiaokang",
    title = "Video Prediction Via Selective Sampling",
    booktitle = "NeurIPS",
    year = "2018"
}
        Finn et al., "Unsupervised Learning For Physical Interaction Through Video Prediction", NeurIPS, 2016. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Finn_2016_NeurIPS,
    author = "Finn, Chelsea and Goodfellow, Ian and Levine, Sergey",
    title = "Unsupervised Learning For Physical Interaction Through Video Prediction",
    booktitle = "NeurIPS",
    year = "2016"
}
      Bibtex 
      @InProceedings{Finn_2016_NeurIPS,
    author = "Finn, Chelsea and Goodfellow, Ian and Levine, Sergey",
    title = "Unsupervised Learning For Physical Interaction Through Video Prediction",
    booktitle = "NeurIPS",
    year = "2016"
}
    Basketball Tracking Dataset (BTD) link paper
    • Summary: A dataset of basketball players’ trajectories for 2015-16 NBA games
    • Applications: Trajectory prediction
    • Data type and annotations: Trajectory
    • Task: Sport
      Used in papers
        Hauri et al., "Multi-Modal Trajectory Prediction of NBA Players", WACV, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Hauri_2021_WACV,
    author = "Hauri, Sandro and Djuric, Nemanja and Radosavljevic, Vladan and Vucetic, Slobodan",
    title = "Multi-Modal Trajectory Prediction of {NBA} Players",
    booktitle = "WACV",
    year = "2021"
}
        Felsen et al., "Where Will They Go? Predicting Fine-Grained Adversarial Multi-Agent Motion Using Conditional Variational Autoencoders", ECCV, 2018. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Felsen_2018_ECCV,
    author = "Felsen, Panna and Lucey, Patrick and Ganguly, Sujoy",
    title = "Where Will They Go? Predicting Fine-Grained Adversarial Multi-Agent Motion Using Conditional Variational Autoencoders",
    booktitle = "ECCV",
    year = "2018"
}
        Qi et al., "Imitative Non-Autoregressive Modeling for Trajectory Forecasting and Imputation", CVPR, 2020. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Qi_2020_CVPR,
    author = "Qi, Mengshi and Qin, Jie and Wu, Yu and Yang, Yi",
    title = "Imitative Non-Autoregressive Modeling for Trajectory Forecasting and Imputation",
    booktitle = "CVPR",
    year = "2020"
}
      Bibtex 
      @InProceedings{Felsen_2018_ECCV,
    author = "Felsen, Panna and Lucey, Patrick and Ganguly, Sujoy",
    title = "Where Will They Go? Predicting Fine-Grained Adversarial Multi-Agent Motion Using Conditional Variational Autoencoders",
    booktitle = "ECCV",
    year = "2018"
}
    BEHAVE link paper arxiv
    • Summary: A dataset of full body human-object interaction with multi view RGBD images recorded using 8 subjects and 20 objects, consisting of 321 videos.
    • Applications:
    • Data type and annotations: RGBD, 3D Mesh
    • Task: Activity
      Used in papers
        Yan et al., "Forecasting of 3D Whole-body Human Poses with Grasping Objects", CVPR, 2024. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Yan_Forecasting_2024_CVPR,
    author = "Yan, Haitao and Cui, Qiongjie and Xie, Jiexin and Guo, Shijie",
    title = "Forecasting of 3D Whole-body Human Poses with Grasping Objects",
    booktitle = "CVPR",
    year = "2024"
}
      Bibtex 
      @InProceedings{Bhatnagar_BEHAVE_2022_CVPR,
    author = "Bhatnagar, Bharat Lal and Xie, Xianghui and Petrov, Ilya A. and Sminchisescu, Cristian and Theobalt, Christian and Pons-Moll, Gerard",
    title = "BEHAVE: Dataset and Method for Tracking Human Object Interactions",
    booktitle = "CVPR",
    year = "2022"
}
    Berkeley DeepDrive (BDD100K) link paper arxiv
    • Summary: A dataset of 100K driving sequences with annotations fo 10 traffic objects annotated at 10Hz
    • Applications: Video prediction
    • Data type and annotations: RGB, Bounding Box, Semantic Segment, Lane Marking, Drivable Areas
    • Task: Driving
      Used in papers
        Schmeckpeper et al., "Learning Predictive Models From Observation and Interaction", ECCV, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Schmeckpeper_2020_ECCV,
    author = "Schmeckpeper, Karl and Xie, Annie and Rybkin, Oleh and Tian, Stephen and Daniilidis, Kostas and Levine, Sergey and Finn, Chelsea",
    title = "Learning Predictive Models From Observation and Interaction",
    booktitle = "ECCV",
    year = "2020"
}
      Bibtex 
      @InProceedings{Xu_2017_CVPR,
    author = "Xu, Huazhe and Gao, Yang and Yu, Fisher and Darrell, Trevor",
    title = "End-To-End Learning of Driving Models From Large-Scale Video Datasets",
    booktitle = "CVPR",
    year = "2017"
}
    Best Track link paper
    • Summary: A dataset of global tropical cyclones collected over 20 years.
    • Applications: Trajectory prediction
    • Data type and annotations: RGB, Trajectory
    • Task: Weather
      Used in papers
        Park et al., "Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data", ICLR, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @inproceedings{Park_longterm_2024_ICLR,
    author = "Park, Young-Jae and Seo, Minseok and Kim, Doyi and Kim, Hyeri and Choi, Sanghoon and Choi, Beomkyu and Ryu, Jeongwon and Son, Sohee and Jeon, Hae-Gon and Choi, Yeji",
    title = "Long-Term Typhoon Trajectory Prediction: A Physics-Conditioned Approach Without Reanalysis Data",
    booktitle = "ICLR",
    year = "2024"
}
      Bibtex 
      @article{Knapp_international_2010_BAMS,
    author = "Knapp, Kenneth R and Kruk, Michael C and Levinson, David H and Diamond, Howard J and Neumann, Charles J",
    title = "The international best track archive for climate stewardship (IBTrACS) unifying tropical cyclone data",
    journal = "Bulletin of the American Meteorological Society",
    volume = "91",
    number = "3",
    pages = "363--376",
    year = "2010"
}
    Bimanual Actions link paper arxiv
    • Summary: A dataset of 540 recordings of 6 subjects performing 9 basic tasks
    • Applications: Video prediction
    • Data type and annotations: RGB, Activity Label, Bounding Box
    • Task: Object interaction
      Used in papers
        Bodla et al., "Hierarchical Video Prediction Using Relational Layouts for Human-Object Interactions", CVPR, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Bodla_2021_CVPR,
    author = "Bodla, Navaneeth and Shrivastava, Gaurav and Chellappa, Rama and Shrivastava, Abhinav",
    title = "Hierarchical Video Prediction Using Relational Layouts for Human-Object Interactions",
    booktitle = "CVPR",
    year = "2021"
}
        Lagamtzis et al., "Exploiting Spatio-Temporal Human-Object Relations Using Graph Neural Networks for Human Action Recognition and 3D Motion Forecasting", IROS, 2023. paper
          Datasets Metrics
          Bibtex 
          @INPROCEEDINGS{Lagamtzis_2023_IROS,
    author = "Lagamtzis, Dimitrios and Schmidt, Fabian and Seyler, Jan and Dang, Thao and Schober, Steffen",
    booktitle = "IROS",
    title = "Exploiting Spatio-Temporal Human-Object Relations Using Graph Neural Networks for Human Action Recognition and 3D Motion Forecasting",
    year = "2023"
}
      Bibtex 
      @Article{Dreher_2020_RAL,
    author = "Dreher, C. R. G. and Wächter, Mirko and Asfour, Tamim",
    journal = "RAL",
    title = "Learning Object-Action Relations from Bimanual Human Demonstration Using Graph Networks",
    year = "2020",
    volume = "5",
    number = "1",
    pages = "187-194"
}
    BIT link paper
    • Summary: A dataset of human interactions with 400 video clips capturing 8 different interaction classes
    • Applications: Action prediction
    • Data type and annotations: RGB, activity label
    • Task: Interaction
      Used in papers
        Zhao et al., "Spatiotemporal Feature Residual Propagation For Action Prediction", ICCV, 2019. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhao_2019_ICCV,
    author = "Zhao, He and Wildes, Richard P.",
    title = "Spatiotemporal Feature Residual Propagation For Action Prediction",
    booktitle = "ICCV",
    year = "2019"
}
        Chen et al., "Part-Activated Deep Reinforcement Learning For Action Prediction", ECCV, 2018. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Chen_2018_ECCV,
    author = "Chen, Lei and Lu, Jiwen and Song, Zhanjie and Zhou, Jie",
    title = "Part-Activated Deep Reinforcement Learning For Action Prediction",
    booktitle = "ECCV",
    year = "2018"
}
        Kong et al., "Deep Sequential Context Networks For Action Prediction", CVPR, 2017. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Kong_2017_CVPR,
    author = "Kong, Yu and Tao, Zhiqiang and Fu, Yun",
    title = "Deep Sequential Context Networks For Action Prediction",
    booktitle = "CVPR",
    year = "2017"
}
        Lee et al., "Human Activity Prediction Based On Sub-Volume Relationship Descriptor", ICPR, 2016. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Lee_2016_ICPR,
    author = "Lee, Dong-Gyu and Lee, Seong-Whan",
    booktitle = "ICPR",
    title = "Human Activity Prediction Based On Sub-Volume Relationship Descriptor",
    year = "2016"
}
      Bibtex 
      @InProceedings{Kong_2012_ECCV,
    author = "Kong, Yu and Jia, Yunde and Fu, Yun",
    year = "2012",
    booktitle = "ECCV",
    title = "Learning Human Interaction By Interactive Phrases"
}
    Bouncing Ball (BB) link paper arxiv
    • Summary: A simulated dataset of bounding balls generated using Neural Physics Engine
    • Applications: Video prediction
    • Data type and annotations: RGB
    • Task: Object (simulation)
      Used in papers
        Hsieh et al., "Learning To Decompose And Disentangle Representations For Video Prediction", NeurIPS, 2018. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Hsieh_2018_NeurIPS,
    author = "Hsieh, Jun-Ting and Liu, Bingbin and Huang, De-An and Fei-Fei, Li F and Niebles, Juan Carlos",
    title = "Learning To Decompose And Disentangle Representations For Video Prediction",
    booktitle = "NeurIPS",
    year = "2018"
}
      Bibtex 
      @Article{Chang_2016_arxiv,
    author = "Chang, Michael B and Ullman, Tomer and Torralba, Antonio and Tenenbaum, Joshua B",
    title = "A Compositional Object-Based Approach To Learning Physical Dynamics",
    journal = "arXiv:1612.00341",
    year = "2016"
}
    Brain4Cars link paper arxiv
    • Summary: A dataset of 700 driving events using inside and outside looking cameras with annotated actions for various driving maneuvers
    • Applications: Action prediction
    • Data type and annotations: RGB, bounding box, attribute, temporal segment, vehicle sensors
    • Task: Driving
      Used in papers
        Kung et al., "Looking Inside Out: Anticipating Driver Intent From Videos", ICRA, 2024. paper arxiv code
          Datasets Metrics
          Bibtex 
          @inproceedings{Kung_looking_2024_ICRA,
    author = "Kung, Yung-Chi and Zhang, Arthur and Wang, Junmin and Biswas, Joydeep",
    booktitle = "ICRA",
    title = "Looking Inside Out: Anticipating Driver Intent From Videos",
    year = "2024"
}
        Jain et al., "Structural-RNN: Deep Learning On Spatio-Temporal Graphs", CVPR, 2016. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Jain_2016_CVPR,
    author = "Jain, Ashesh and Zamir, Amir R. and Savarese, Silvio and Saxena, Ashutosh",
    title = "{Structural-RNN}: Deep Learning On Spatio-Temporal Graphs",
    booktitle = "CVPR",
    year = "2016"
}
        Jain et al., "Recurrent Neural Networks For Driver Activity Anticipation Via Sensory-Fusion Architecture", ICRA, 2016. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Jain_2016_ICRA,
    author = "Jain, A. and Singh, A. and Koppula, H. S. and Soh, S. and Saxena, A.",
    booktitle = "ICRA",
    title = "Recurrent Neural Networks For Driver Activity Anticipation Via Sensory-Fusion Architecture",
    year = "2016"
}
        Jain et al., "Car That Knows Before You Do: Anticipating Maneuvers Via Learning Temporal Driving Models", ICCV, 2015. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Jain_2015_ICCV,
    author = "Jain, Ashesh and Koppula, Hema S. and Raghavan, Bharad and Soh, Shane and Saxena, Ashutosh",
    title = "Car That Knows Before You Do: Anticipating Maneuvers Via Learning Temporal Driving Models",
    booktitle = "ICCV",
    year = "2015"
}
      Bibtex 
      @InProceedings{Jain_2015_ICCV,
    author = "Jain, Ashesh and Koppula, Hema S. and Raghavan, Bharad and Soh, Shane and Saxena, Ashutosh",
    title = "Car That Knows Before You Do: Anticipating Maneuvers Via Learning Temporal Driving Models",
    booktitle = "ICCV",
    year = "2015"
}
    Breakfast link paper
    • Summary: A dataset of 77 hours of a video recording showing 10 breakfast preparation actions performed by 52 subjects in 18 different locations
    • Applications: Action prediction
    • Data type and annotations: RGB, activity label, temporal segment
    • Task: Cooking
      Used in papers
        Girase et al., "Latency Matters: Real-Time Action Forecasting Transformer", CVPR, 2023. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Girase_2023_CVPR,
    author = "Girase, Harshayu and Agarwal, Nakul and Choi, Chiho and Mangalam, Karttikeya",
    title = "Latency Matters: Real-Time Action Forecasting Transformer",
    booktitle = "CVPR",
    year = "2023"
}
        Nawhal et al., "Rethinking Learning Approaches for Long-Term Action Anticipation", ECCV, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Nawhal_2022_ECCV,
    author = "Nawhal, Megha and Jyothi, Akash Abdu and Mori, Greg",
    title = "Rethinking Learning Approaches for Long-Term Action Anticipation",
    booktitle = "ECCV",
    year = "2022"
}
        Roy et al., "Action Anticipation Using Latent Goal Learning", WACV, 2022. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Roy_2022_WACV,
    author = "Roy, Debaditya and Fernando, Basura",
    title = "Action Anticipation Using Latent Goal Learning",
    booktitle = "WACV",
    year = "2022"
}
        Zhao et al., "On Diverse Asynchronous Activity Anticipation", ECCV, 2020. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhao_2020_ECCV,
    author = "Zhao, He and Wildes, Richard P.",
    title = "On Diverse Asynchronous Activity Anticipation",
    booktitle = "ECCV",
    year = "2020"
}
        Morais et al., "Learning to Abstract and Predict Human Actions", BMVC, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Morais_2020_BMVC,
    author = "Morais, Romero and Le, Vuong and Tran, Truyen and Venkatesh, Svetha",
    title = "Learning to Abstract and Predict Human Actions",
    booktitle = "BMVC",
    year = "2020"
}
        Gammulle et al., "Forecasting Future Action Sequences With Neural Memory Networks", BMVC, 2019. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Gammulle_2019_BMVC,
    author = "Gammulle, Harshala and Denman, Simon and Sridharan, Sridha and Fookes, Clinton",
    title = "Forecasting Future Action Sequences With Neural Memory Networks",
    year = "2019",
    booktitle = "BMVC"
}
        Alati et al., "Help By Predicting What To Do", ICIP, 2019. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Alati_2019_ICIP,
    author = "Alati, E. and Mauro, L. and Ntouskos, V. and Pirri, F.",
    booktitle = "ICIP",
    title = "Help By Predicting What To Do",
    year = "2019"
}
        Abu et al., "When Will You Do What? - Anticipating Temporal Occurrences Of Activities", CVPR, 2018. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Farha_2018_CVPR,
    author = "Abu Farha, Yazan and Richard, Alexander and Gall, Juergen",
    title = "When Will You Do What? - Anticipating Temporal Occurrences Of Activities",
    booktitle = "CVPR",
    year = "2018"
}
      Bibtex 
      @InProceedings{Kuehne_2014_CVPR,
    author = "Kuehne, H. and Arslan, A. B. and Serre, T.",
    title = "The Language Of Actions: Recovering The Syntax And Semantics Of Goal-Directed Human Activities",
    booktitle = "CVPR",
    year = "2014"
}
    BridgeData link paper arxiv
    • Summary: A dataset of robot manipulation with 60K+ trajectories consisting of 13 skills performed in 24 environments.
    • Applications:
    • Data type and annotations: RGB, Activity label
    • Task: Robot object manipulation
      Used in papers
        Gu et al., "Seer: Language Instructed Video Prediction with Latent Diffusion Models", ICLR, 2024. paper arxiv code
          Datasets Metrics
          Bibtex 
          @inproceedings{Gu_seer_2024_ICLR,
    author = "Gu, Xianfan and Wen, Chuan and Ye, Weirui and Song, Jiaming and Gao, Yang",
    title = "Seer: Language Instructed Video Prediction with Latent Diffusion Models",
    booktitle = "ICLR",
    year = "2024"
}
      Bibtex 
      @inproceedings{Walke_bridgedata_2023_CoRL,
    author = "Walke, Homer Rich and Black, Kevin and Zhao, Tony Z. and Vuong, Quan and Zheng, Chongyi and Hansen-Estruch, Philippe and He, Andre Wang and Myers, Vivek and Kim, Moo Jin and Du, Max and Lee, Abraham and Fang, Kuan and Finn, Chelsea and Levine, Sergey",
    title = "BridgeData V2: A Dataset for Robot Learning at Scale",
    booktitle = "CoRL",
    year = "2023"
}
    BU Action (BUA) link paper arxiv
    • Summary: A dataset of action images with 23K+ images and 101 activity classes collected from existing action video datasets
    • Applications: Action prediction
    • Data type and annotations: RGB, activity label
    • Task: Activity
      Used in papers
        Safaei et al., "Still Image Action Recognition By Predicting Spatial-Temporal Pixel Evolution", WACV, 2019. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Safaei_2019_WACV,
    author = "Safaei, M. and Foroosh, H.",
    booktitle = "WACV",
    title = "Still Image Action Recognition By Predicting Spatial-Temporal Pixel Evolution",
    year = "2019"
}
      Bibtex 
      @Article{Ma_2017_PR,
    author = "Ma, Shugao and Bargal, Sarah Adel and Zhang, Jianming and Sigal, Leonid and Sclaroff, Stan",
    title = "Do Less And Achieve More: Training Cnns For Action Recognition Utilizing Action Images From The Web",
    journal = "Pattern Recognition",
    volume = "68",
    pages = "334--345",
    year = "2017"
}
    CAD-120 link paper arxiv
    • Summary: A dataset of 120 RGBD videos of 10 daily activities performed by 4 subjects
    • Applications: Action prediction
    • Data type and annotations: RGBD, 3D pose, activity label, affordance label
    • Task: Activity
      Used in papers
        Alati et al., "Help By Predicting What To Do", ICIP, 2019. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Alati_2019_ICIP,
    author = "Alati, E. and Mauro, L. and Ntouskos, V. and Pirri, F.",
    booktitle = "ICIP",
    title = "Help By Predicting What To Do",
    year = "2019"
}
        Schydlo et al., "Anticipation In Human-Robot Cooperation: A Recurrent Neural Network Approach For Multiple Action Sequences Prediction", ICRA, 2018. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Schydlo_2018_ICRA_2,
    author = "Schydlo, P. and Rakovic, M. and Jamone, L. and Santos-Victor, J.",
    booktitle = "ICRA",
    title = "Anticipation In Human-Robot Cooperation: A Recurrent Neural Network Approach For Multiple Action Sequences Prediction",
    year = "2018"
}
        Qi et al., "Predicting Human Activities Using Stochastic Grammar", ICCV, 2017. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Qi_2017_ICCV,
    author = "Qi, Siyuan and Huang, Siyuan and Wei, Ping and Zhu, Song-Chun",
    title = "Predicting Human Activities Using Stochastic Grammar",
    booktitle = "ICCV",
    year = "2017"
}
        Jain et al., "Structural-RNN: Deep Learning On Spatio-Temporal Graphs", CVPR, 2016. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Jain_2016_CVPR,
    author = "Jain, Ashesh and Zamir, Amir R. and Savarese, Silvio and Saxena, Ashutosh",
    title = "{Structural-RNN}: Deep Learning On Spatio-Temporal Graphs",
    booktitle = "CVPR",
    year = "2016"
}
        Hu et al., "Human Intent Forecasting Using Intrinsic Kinematic Constraints", IROS, 2016. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Hu_2016_IROS,
    author = "Hu, N. and Bestick, A. and Englebienne, G. and Bajscy, R. and Kröse, B.",
    booktitle = "IROS",
    title = "Human Intent Forecasting Using Intrinsic Kinematic Constraints",
    year = "2016"
}
      Bibtex 
      @Article{Koppula_2013_IJRR,
    author = "Koppula, Hema Swetha and Gupta, Rudhir and Saxena, Ashutosh",
    title = "Learning Human Activities And Object Affordances From {RGB-D} Videos",
    journal = "IJRR",
    volume = "32",
    number = "8",
    pages = "951--970",
    year = "2013"
}
    Caltech Pedestrian link paper
    • Summary: A pedestrian detection dataset with 2.3K unique samples with approx. 10 hours of video footage recorded and annotated at 30hz
    • Applications: Video prediction, Action prediction
    • Data type and annotations: RGB, bounding box, Tracking ID
    • Task: Driving
      Used in papers
        Gao et al., "SimVP: Simpler Yet Better Video Prediction", CVPR, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Gao_2022_CVPR,
    author = "Gao, Zhangyang and Tan, Cheng and Wu, Lirong and Li, Stan Z.",
    title = "{SimVP}: Simpler Yet Better Video Prediction",
    booktitle = "CVPR",
    year = "2022"
}
        Geng et al., "Comparing Correspondences: Video Prediction With Correspondence-Wise Losses", CVPR, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Geng_2022_CVPR,
    author = "Geng, Daniel and Hamilton, Max and Owens, Andrew",
    title = "Comparing Correspondences: Video Prediction With Correspondence-Wise Losses",
    booktitle = "CVPR",
    year = "2022"
}
        Chang et al., "MAU: A Motion-Aware Unit for Video Prediction and Beyond", NeurIPS, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Chang_2021_NeurIPS,
    author = "Chang, Zheng and Zhang, Xinfeng and Wang, Shanshe and Ma, Siwei and Ye, Yan and Xinguang, Xiang and Gao, Wen",
    booktitle = "NeurIPS",
    title = "{MAU}: A Motion-Aware Unit for Video Prediction and Beyond",
    year = "2021"
}
        Jin et al., "Exploring Spatial-Temporal Multi-Frequency Analysis for High-Fidelity and Temporal-Consistency Video Prediction", CVPR, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Jin_2020_CVPR,
    author = "Jin, Beibei and Hu, Yu and Tang, Qiankun and Niu, Jingyu and Shi, Zhiping and Han, Yinhe and Li, Xiaowei",
    title = "Exploring Spatial-Temporal Multi-Frequency Analysis for High-Fidelity and Temporal-Consistency Video Prediction",
    booktitle = "CVPR",
    year = "2020"
}
        Kwon et al., "Predicting Future Frames Using Retrospective Cycle GAN", CVPR, 2019. paper
        Gao et al., "Disentangling Propagation And Generation For Video Prediction", ICCV, 2019. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Gao_2019_ICCV,
    author = "Gao, Hang and Xu, Huazhe and Cai, Qi-Zhi and Wang, Ruth and Yu, Fisher and Darrell, Trevor",
    title = "Disentangling Propagation And Generation For Video Prediction",
    booktitle = "ICCV",
    year = "2019"
}
        Ho et al., "SME-Net: Sparse Motion Estimation For Parametric Video Prediction Through Reinforcement Learning", ICCV, 2019. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Ho_2019_ICCV,
    author = "Ho, Yung-Han and Cho, Chuan-Yuan and Peng, Wen-Hsiao and Jin, Guo-Lun",
    title = "{SME-Net}: Sparse Motion Estimation For Parametric Video Prediction Through Reinforcement Learning",
    booktitle = "ICCV",
    year = "2019"
}
        Ho et al., "Deep Reinforcement Learning For Video Prediction", ICIP, 2019. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Ho_2019_ICIP,
    author = "Ho, Y. and Cho, C. and Peng, W.",
    booktitle = "ICIP",
    title = "Deep Reinforcement Learning For Video Prediction",
    year = "2019"
}
        Byeon et al., "Contextvp: Fully Context-Aware Video Prediction", ECCV, 2018. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Byeon_2018_ECCV,
    author = "Byeon, Wonmin and Wang, Qin and Kumar Srivastava, Rupesh and Koumoutsakos, Petros",
    title = "Contextvp: Fully Context-Aware Video Prediction",
    booktitle = "ECCV",
    year = "2018"
}
        Liu et al., "Dyan: A Dynamical Atoms-Based Network For Video Prediction", ECCV, 2018. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Liu_2018_ECCV,
    author = "Liu, Wenqian and Sharma, Abhishek and Camps, Octavia and Sznaier, Mario",
    title = "Dyan: A Dynamical Atoms-Based Network For Video Prediction",
    booktitle = "ECCV",
    year = "2018"
}
        Reda et al., "SDC-Net: Video Prediction Using Spatially-Displaced Convolution", ECCV, 2018. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Reda_2018_ECCV,
    author = "Reda, Fitsum A. and Liu, Guilin and Shih, Kevin J. and Kirby, Robert and Barker, Jon and Tarjan, David and Tao, Andrew and Catanzaro, Bryan",
    title = "{SDC-Net}: Video Prediction Using Spatially-Displaced Convolution",
    booktitle = "ECCV",
    year = "2018"
}
        Liang et al., "Dual Motion GAN For Future-Flow Embedded Video Prediction", ICCV, 2017. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Liang_2017_ICCV,
    author = "Liang, Xiaodan and Lee, Lisa and Dai, Wei and Xing, Eric P.",
    title = "Dual Motion {GAN} For Future-Flow Embedded Video Prediction",
    booktitle = "ICCV",
    year = "2017"
}
        Hariyono et al., "Estimation Of Collision Risk For Improving Driver's Safety", IECON, 2016. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Hariyono_2016_IES,
    author = "Hariyono, Joko and Shahbaz, Ajmal and Kurnianggoro, Laksono and Jo, Kang-Hyun",
    title = "Estimation Of Collision Risk For Improving Driver's Safety",
    booktitle = "IECON",
    year = "2016"
}
      Bibtex 
      @InProceedings{Dollar_2009_CVPR,
    author = "Doll\'ar, P. and Wojek, C. and Schiele, B. and Perona, P.",
    title = "Pedestrian Detection: A Benchmark",
    booktitle = "CVPR",
    year = "2009"
}
    Campus and Shelf (CaS) link paper
    • Summary: A dataset of multiple actors engaging in group activities with associated 3D poses recorded in two different environments.
    • Applications: Motion prediction
    • Data type and annotations: 3D Pose, RGB
    • Task: Activity
      Used in papers
        Choudhury et al., "TEMPO: Efficient Multi-View Pose Estimation, Tracking, and Forecasting", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Choudhury_2023_ICCV,
    author = "Choudhury, Rohan and Kitani, Kris M. and Jeni, Laszlo A.",
    title = "TEMPO: Efficient Multi-View Pose Estimation, Tracking, and Forecasting",
    booktitle = "ICCV",
    year = "2023"
}
      Bibtex 
      @inproceedings{Belagian_2014_CVPR,
    author = "Belagiannis, Vasileios and Amin, Sikandar and Andriluka, Mykhaylo and Schiele, Bernt and Navab, Nassir and Ilic, Slobodan",
    title = "{3D} Pictorial Structures for Multiple Human Pose Estimation",
    booktitle = "CVPR",
    year = "2014"
}
    Car Pedestrian Interaction (CPI) link paper arxiv
    • Summary: A dataset of simulated cars and pedestrians interacting
    • Applications: Trajectory prediction
    • Data type and annotations: Trajectory, Tracking Id
    • Task: Trajectory
      Used in papers
        Narayanan et al., "Divide-and-Conquer for Lane-Aware Diverse Trajectory Prediction", CVPR, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Narayanan_2021_CVPR,
    author = "Narayanan, Sriram and Moslemi, Ramin and Pittaluga, Francesco and Liu, Buyu and Chandraker, Manmohan",
    title = "Divide-and-Conquer for Lane-Aware Diverse Trajectory Prediction",
    booktitle = "CVPR",
    year = "2021"
}
        Makansi et al., "Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction", CVPR, 2019. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Makansi_2019_CVPR,
    author = "Makansi, Osama and Ilg, Eddy and Cicek, Ozgun and Brox, Thomas",
    title = "Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction",
    booktitle = "CVPR",
    year = "2019"
}
      Bibtex 
      @InProceedings{Makansi_2019_CVPR,
    author = "Makansi, Osama and Ilg, Eddy and Cicek, Ozgun and Brox, Thomas",
    title = "Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction",
    booktitle = "CVPR",
    year = "2019"
}
    CARLA link paper arxiv
    • Summary: A dataset of 900 simulated driving segments for multi-agent trajectory forecasting and planning
    • Applications: Action prediction
    • Data type and annotations: RGB
    • Task: Driving (simulation)
      Used in papers
        Filatov et al., "Any Motion Detector: Learning Class-agnostic Scene Dynamics from a Sequence of LiDAR Point Clouds", ICRA, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Filatov_2020_ICRA,
    author = "Filatov, A. and Rykov, A. and Murashkin, V.",
    booktitle = "ICRA",
    title = "Any Motion Detector: Learning Class-agnostic Scene Dynamics from a Sequence of {LiDAR} Point Clouds",
    year = "2020"
}
        Diehl et al., "Energy-based Potential Games for Joint Motion Forecasting and Control", CoRL, 2023. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Diehl_2023_CoRL,
    author = "Diehl, Christopher and Klosek, Tobias and Krueger, Martin and Murzyn, Nils and Osterburg, Timo and Bertram, Torsten",
    title = "Energy-based Potential Games for Joint Motion Forecasting and Control",
    booktitle = "CoRL",
    year = "2023"
}
        Roh et al., "Multimodal Trajectory Prediction via Topological Invariance for Navigation at Uncontrolled Intersections", CoRL, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Roh_2020_CORL,
    author = "Roh, Junha and Mavrogiannis, Christoforos and Madan, Rishabh and Fox, Dieter and Srinivasa, Siddhartha S",
    title = "Multimodal Trajectory Prediction via Topological Invariance for Navigation at Uncontrolled Intersections",
    booktitle = "CoRL",
    year = "2020"
}
        Rhinehart et al., "Precog: Prediction Conditioned On Goals In Visual Multi-Agent Settings", ICCV, 2019. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Rhinehart_2019_ICCV,
    author = "Rhinehart, Nicholas and McAllister, Rowan and Kitani, Kris and Levine, Sergey",
    title = "Precog: Prediction Conditioned On Goals In Visual Multi-Agent Settings",
    booktitle = "ICCV",
    year = "2019"
}
        Tang et al., "Multiple futures prediction", NeurIPS, 2019. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Tang_2019_NeurIPS,
    author = "Tang, Charlie and Salakhutdinov, Russ R",
    title = "Multiple futures prediction",
    booktitle = "NeurIPS",
    year = "2019"
}
        Ding et al., "Online Vehicle Trajectory Prediction Using Policy Anticipation Network And Optimization-Based Context Reasoning", ICRA, 2019. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Ding_2019_ICRA_2,
    author = "Ding, W. and Shen, S.",
    booktitle = "ICRA",
    title = "Online Vehicle Trajectory Prediction Using Policy Anticipation Network And Optimization-Based Context Reasoning",
    year = "2019"
}
        Hu et al., "Safe Local Motion Planning With Self-Supervised Freespace Forecasting", CVPR, 2021. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Hu_2021_CVPR,
    author = "Hu, Peiyun and Huang, Aaron and Dolan, John and Held, David and Ramanan, Deva",
    title = "Safe Local Motion Planning With Self-Supervised Freespace Forecasting",
    booktitle = "CVPR",
    year = "2021"
}
        Oh et al., "HCNAF: Hyper-Conditioned Neural Autoregressive Flow and its Application for Probabilistic Occupancy Map Forecasting", CVPR, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Oh_2020_CVPR,
    author = "Oh, Geunseob and Valois, Jean-Sebastien",
    title = "{HCNAF}: Hyper-Conditioned Neural Autoregressive Flow and its Application for Probabilistic Occupancy Map Forecasting",
    booktitle = "CVPR",
    year = "2020"
}
      Bibtex 
      @InProceedings{Rhinehart_2019_ICCV,
    author = "Rhinehart, Nicholas and McAllister, Rowan and Kitani, Kris and Levine, Sergey",
    title = "Precog: Prediction Conditioned On Goals In Visual Multi-Agent Settings",
    booktitle = "ICCV",
    year = "2019"
}
    Ceilidh Dance link paper
    • Summary: A dataset of Ceilidh Scottish dance sequences performed by 16 dancers in two styles recorded from bird’s eye view.
    • Applications: Action prediction, Trajectory prediction
    • Data type and annotations: RGB, Activity Label, Trajectory
    • Task: Activity
      Used in papers
        Hu et al., "Entry-Flipped Transformer for Inference and Prediction of Participant Behavior", ECCV, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Hu_2022_ECCV,
    author = "Hu, Bo and Cham, Tat-Jen",
    title = "Entry-Flipped Transformer for Inference and Prediction of Participant Behavior",
    booktitle = "ECCV",
    year = "2022"
}
      Bibtex 
      @mastersthesis{Aizeboje_2016_masc,
    author = "Aizeboje, Jeremiah",
    title = "Ceilidh Dance Recognition from an Overhead Camera",
    year = "2016",
    school = "University of Edinburgh"
}
    Charades link paper arxiv
    • Summary: A dataset of ~10K indoor videos with 157 action and 46 object classes
    • Applications: Action prediction
    • Data type and annotations: RGB, Activity label, Object Class, Temporal segment
    • Task: Activity
      Used in papers
        Piergiovanni et al., "Adversarial Generative Grammars for Human Activity Prediction", ECCV, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Piergiovanni_2020_ECCV,
    author = "Piergiovanni, AJ and Angelova, Anelia and Toshev, Alexander and Ryoo, Michael S",
    title = "Adversarial Generative Grammars for Human Activity Prediction",
    booktitle = "ECCV",
    year = "2020"
}
      Bibtex 
      @InProceedings{Sigurdsson_2016_ECCV,
    author = {Sigurdsson, Gunnar A and Varol, G{\"u}l and Wang, Xiaolong and Farhadi, Ali and Laptev, Ivan and Gupta, Abhinav},
    title = "Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding",
    booktitle = "ECCV",
    year = "2016"
}
    Charges link paper arxiv
    • Summary: A physics-based simulation of particles.
    • Applications: Trajectory prediction
    • Data type and annotations: Trajectory
    • Task: Simulation
      Used in papers
        Li et al., "GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction", NeurIPS, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Li_2021_NeurIPS,
    author = "Li, Longyuan and Yao, Jian and Wenliang, Li and He, Tong and Xiao, Tianjun and Yan, Junchi and Wipf, David and Zhang, Zheng",
    booktitle = "NeurIPS",
    title = "{GRIN}: Generative Relation and Intention Network for Multi-agent Trajectory Prediction",
    year = "2021"
}
        Xu et al., "Tra2Tra: Trajectory-to-Trajectory Prediction With a Global Social Spatial-Temporal Attentive Neural Network", RAL, 2021. paper
          Datasets Metrics
          Bibtex 
          @Article{Xu_2021_RAL,
    author = "Xu, Yi and Ren, Dongchun and Li, Mingxia and Chen, Yuehai and Fan, Mingyu and Xia, Huaxia",
    journal = "RAL",
    title = "Tra2Tra: Trajectory-to-Trajectory Prediction With a Global Social Spatial-Temporal Attentive Neural Network",
    year = "2021",
    volume = "6",
    number = "2",
    pages = "1574-1581"
}
        Kamra et al., "Multi-agent Trajectory Prediction with Fuzzy Query Attention", NeurIPS, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Kamra_2020_NeurIPS,
    author = "Kamra, Nitin and Zhu, Hao and Trivedi, Dweep Kumarbhai and Zhang, Ming and Liu, Yan",
    editor = "Larochelle, H. and Ranzato, M. and Hadsell, R. and Balcan, M. F. and Lin, H.",
    booktitle = "NeurIPS",
    title = "Multi-agent Trajectory Prediction with Fuzzy Query Attention",
    year = "2020"
}
        Kipf et al., "Neural Relational Inference for Interacting Systems", ICML, 2018. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Kipf_2018_ICML,
    author = "Kipf, Thomas and Fetaya, Ethan and Wang, Kuan-Chieh and Welling, Max and Zemel, Richard",
    title = "Neural Relational Inference for Interacting Systems",
    booktitle = "ICML",
    year = "2018"
}
      Bibtex 
      @InProceedings{Kipf_2018_ICML,
    author = "Kipf, Thomas and Fetaya, Ethan and Wang, Kuan-Chieh and Welling, Max and Zemel, Richard",
    title = "Neural Relational Inference for Interacting Systems",
    booktitle = "ICML",
    year = "2018"
}
    CityPersons link paper arxiv
    • Summary: A subset of Cityscapes dataset with fine-grained annotations for pedestrians and vehicles in additional 20K images with a total of 35K+ bounding boxes for pedestrians
    • Applications: Trajectory prediction
    • Data type and annotations: Stereo RGB, bounding box, semantic segment
    • Task: Driving
      Used in papers
        Bhattacharyya et al., "Long-Term On-Board Prediction Of People In Traffic Scenes Under Uncertainty", CVPR, 2018. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Bhattacharyya_2018_CVPR,
    author = "Bhattacharyya, Apratim and Fritz, Mario and Schiele, Bernt",
    title = "Long-Term On-Board Prediction Of People In Traffic Scenes Under Uncertainty",
    booktitle = "CVPR",
    year = "2018"
}
      Bibtex 
      @InProceedings{Shanshan_2017_CVPR,
    Author = "Zhang, Shanshan and Benenson, Rodrigo and Schiele, Bernt",
    Title = "Citypersons: A Diverse Dataset For Pedestrian Detection",
    Booktitle = "CVPR",
    Year = "2017"
}
    Cityscapes link paper arxiv
    • Summary: A driving dataset of street images with annotations for 30 traffic objects in 5k frames and weak annotations in 20k frames
    • Applications: Video prediction, Trajectory prediction, Other prediction
    • Data type and annotations: Stereo RGB, bounding box, semantic segment, vehicle sensors
    • Task: Driving
      Used in papers
        Zhang et al., "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction", CVPR, 2024. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhang_ExtDM_2024_CVPR,
    author = "Zhang, Zhicheng and Hu, Junyao and Cheng, Wentao and Paudel, Danda and Yang, Jufeng",
    title = "ExtDM: Distribution Extrapolation Diffusion Model for Video Prediction",
    booktitle = "CVPR",
    year = "2024"
}
        Hu et al., "A Dynamic Multi-Scale Voxel Flow Network for Video Prediction", CVPR, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Hu_2023_CVPR,
    author = "Hu, Xiaotao and Huang, Zhewei and Huang, Ailin and Xu, Jun and Zhou, Shuchang",
    title = "A Dynamic Multi-Scale Voxel Flow Network for Video Prediction",
    booktitle = "CVPR",
    year = "2023"
}
        Geng et al., "Comparing Correspondences: Video Prediction With Correspondence-Wise Losses", CVPR, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Geng_2022_CVPR,
    author = "Geng, Daniel and Hamilton, Max and Owens, Andrew",
    title = "Comparing Correspondences: Video Prediction With Correspondence-Wise Losses",
    booktitle = "CVPR",
    year = "2022"
}
        Wu et al., "Optimizing Video Prediction via Video Frame Interpolation", CVPR, 2022. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Wu_2022_CVPR,
    author = "Wu, Yue and Wen, Qiang and Chen, Qifeng",
    title = "Optimizing Video Prediction via Video Frame Interpolation",
    booktitle = "CVPR",
    year = "2022"
}
        Lee et al., "Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction", ICLR, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Wonkwang_2021_ICLR,
    author = "Lee, Wonkwang and Jung, Whie and Zhang, Han and Chen, Ting and Koh, Jing Yu and Huang, Thomas and Yoon, Hyungsuk and Lee, Honglak and Hong, Seunghoon",
    booktitle = "ICLR",
    title = "Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction",
    year = "2021"
}
        Bei et al., "Learning Semantic-Aware Dynamics for Video Prediction", CVPR, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Bei_2021_CVPR,
    author = "Bei, Xinzhu and Yang, Yanchao and Soatto, Stefano",
    title = "Learning Semantic-Aware Dynamics for Video Prediction",
    booktitle = "CVPR",
    year = "2021"
}
        Wu et al., "Future Video Synthesis With Object Motion Prediction", CVPR, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Wu_2020_CVPR,
    author = "Wu, Yue and Gao, Rongrong and Park, Jaesik and Chen, Qifeng",
    title = "Future Video Synthesis With Object Motion Prediction",
    booktitle = "CVPR",
    year = "2020"
}
        Castrejon et al., "Improved Conditional VRNNs For Video Prediction", ICCV, 2019. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Castrejon_2019_ICCV,
    author = "Castrejon, Lluis and Ballas, Nicolas and Courville, Aaron",
    title = "Improved Conditional {VRNNs} For Video Prediction",
    booktitle = "ICCV",
    year = "2019"
}
        Xu et al., "Structure Preserving Video Prediction", CVPR, 2018. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Xu_2018_CVPR,
    author = "Xu, Jingwei and Ni, Bingbing and Li, Zefan and Cheng, Shuo and Yang, Xiaokang",
    title = "Structure Preserving Video Prediction",
    booktitle = "CVPR",
    year = "2018"
}
        Marchetti et al., "MANTRA: Memory Augmented Networks for Multiple Trajectory Prediction", CVPR, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Marchetti_2020_CVPR,
    author = "Marchetti, Francesco and Becattini, Federico and Seidenari, Lorenzo and Del Bimbo, Alberto",
    title = "{MANTRA}: Memory Augmented Networks for Multiple Trajectory Prediction",
    booktitle = "CVPR",
    year = "2020"
}
        Srikanth et al., "INFER: INtermediate Representations For FuturE PRediction", IROS, 2019. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Srikanth_2019_IROS,
    author = "Srikanth, Shashank and Ansari, Junaid Ahmed and Sharma, Sarthak and others",
    booktitle = "IROS",
    title = "{INFER}: {IN}termediate Representations For {F}utur{E} P{R}ediction",
    year = "2019"
}
        Graber et al., "Joint Forecasting of Panoptic Segmentations With Difference Attention", CVPR, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Graber_2022_CVPR,
    author = "Graber, Colin and Jazra, Cyril and Luo, Wenjie and Gui, Liangyan and Schwing, Alexander G.",
    title = "Joint Forecasting of Panoptic Segmentations With Difference Attention",
    booktitle = "CVPR",
    year = "2022"
}
        Graber et al., "Panoptic Segmentation Forecasting", CVPR, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Graber_2021_CVPR,
    author = "Graber, Colin and Tsai, Grace and Firman, Michael and Brostow, Gabriel and Schwing, Alexander G.",
    title = "Panoptic Segmentation Forecasting",
    booktitle = "CVPR",
    year = "2021"
}
        Lin et al., "Predictive Feature Learning for Future Segmentation Prediction", ICCV, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Lin_2021_ICCV,
    author = "Lin, Zihang and Sun, Jiangxin and Hu, Jian-Fang and Yu, Qizhi and Lai, Jian-Huang and Zheng, Wei-Shi",
    title = "Predictive Feature Learning for Future Segmentation Prediction",
    booktitle = "ICCV",
    year = "2021"
}
        Saric et al., "Warp to the Future: Joint Forecasting of Features and Feature Motion", CVPR, 2020. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Saric_2020_CVPR,
    author = "Saric, Josip and Orsic, Marin and Antunovic, Tonci and Vrazic, Sacha and Segvic, Sinisa",
    title = "Warp to the Future: Joint Forecasting of Features and Feature Motion",
    booktitle = "CVPR",
    year = "2020"
}
        Hu et al., "Probabilistic Future Prediction for Video Scene Understanding", ECCV, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Hu_2020_ECCV,
    author = "Hu, Anthony and Cotter, Fergal and Mohan, Nikhil and Gurau, Corina and Kendall, Alex",
    title = "Probabilistic Future Prediction for Video Scene Understanding",
    booktitle = "ECCV",
    year = "2020"
}
        Terwilliger et al., "Recurrent Flow-Guided Semantic Forecasting", WACV, 2019. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Terwilliger_2019_WACV,
    author = "Terwilliger, A. and Brazil, G. and Liu, X.",
    booktitle = "WACV",
    title = "Recurrent Flow-Guided Semantic Forecasting",
    year = "2019"
}
        Luc et al., "Predicting Future Instance Segmentation By Forecasting Convolutional Features", ECCV, 2018. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Luc_2018_ECCV,
    author = "Luc, Pauline and Couprie, Camille and LeCun, Yann and Verbeek, Jakob",
    title = "Predicting Future Instance Segmentation By Forecasting Convolutional Features",
    booktitle = "ECCV",
    year = "2018"
}
        Luc et al., "Predicting Deeper Into The Future Of Semantic Segmentation", ICCV, 2017. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Luc_2017_ICCV,
    author = "Luc, Pauline and Neverova, Natalia and Couprie, Camille and Verbeek, Jakob and LeCun, Yann",
    title = "Predicting Deeper Into The Future Of Semantic Segmentation",
    booktitle = "ICCV",
    year = "2017"
}
        Jin et al., "Predicting Scene Parsing And Motion Dynamics In The Future", NeurIPS, 2017. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Jin_2017_NeurIPS,
    author = "Jin, Xiaojie and Xiao, Huaxin and Shen, Xiaohui and Yang, Jimei and Lin, Zhe and Chen, Yunpeng and Jie, Zequn and Feng, Jiashi and Yan, Shuicheng",
    title = "Predicting Scene Parsing And Motion Dynamics In The Future",
    booktitle = "NeurIPS",
    year = "2017"
}
      Bibtex 
      @InProceedings{Cordts_2016_CVPR,
    author = "Cordts, Marius and Omran, Mohamed and Ramos, Sebastian and Rehfeld, Timo and Enzweiler, Markus and Benenson, Rodrigo and Franke, Uwe and Roth, Stefan and Schiele, Bernt",
    title = "The Cityscapes Dataset For Semantic Urban Scene Understanding",
    booktitle = "CVPR",
    year = "2016"
}
    CityWalks link paper arxiv
    • Summary: A dataset of 500+ front-view sequences of pedestrian trajectories annotated at 30fps
    • Applications: Trajectory prediction
    • Data type and annotations: RGB, bounding box, attribute, Tracking ID
    • Task: Walking
      Used in papers
        Styles et al., "Multiple Object Forecasting: Predicting Future Object Locations in Diverse Environments", WACV, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Styles_2020_WACV,
    author = "Styles, Oliver and Sanchez, Victor and Guha, Tanaya",
    title = "Multiple Object Forecasting: Predicting Future Object Locations in Diverse Environments",
    booktitle = "WACV",
    year = "2020"
}
        Ansari et al., "Simple means Faster: Real-Time Human Motion Forecasting in Monocular First Person Videos on CPU", IROS, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Ansari_2020_IROS,
    author = "Ansari, J. A. and Bhowmick, B.",
    booktitle = "IROS",
    title = "Simple means Faster: Real-Time Human Motion Forecasting in Monocular First Person Videos on {CPU}",
    year = "2020"
}
      Bibtex 
      @InProceedings{Styles_2020_WACV,
    author = "Styles, Oliver and Sanchez, Victor and Guha, Tanaya",
    title = "Multiple Object Forecasting: Predicting Future Object Locations in Diverse Environments",
    booktitle = "WACV",
    year = "2020"
}
    CMU Mocap link
    • Summary: A motion dataset consists of various activities including human interaction, interaction with the environment, locomotion, sports, etc.
    • Applications: Action prediction, Motion prediction
    • Data type and annotations: 3D pose, activity label
    • Task: Activity
      Used in papers
        Butepage et al., "Deep Representation Learning For Human Motion Prediction And Classification", CVPR, 2017. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Butepage_2017_CVPR,
    author = "Butepage, Judith and Black, Michael J. and Kragic, Danica and Kjellstrom, Hedvig",
    title = "Deep Representation Learning For Human Motion Prediction And Classification",
    booktitle = "CVPR",
    year = "2017"
}
        Dax et al., "Disentangled Neural Relational Inference for Interpretable Motion Prediction", RAL, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @ARTICLE{Dax_Disentangled_2024_RAL,
    author = "Dax, Victoria M. and Li, Jiachen and Sachdeva, Enna and Agarwal, Nakul and Kochenderfer, Mykel J.",
    journal = "RAL",
    title = "Disentangled Neural Relational Inference for Interpretable Motion Prediction",
    year = "2024",
    volume = "9",
    number = "2",
    pages = "1452-1459",
    keywords = "Predictive models;Trajectory;Vehicle dynamics;Decoding;Data models;Computational modeling;Training;AI-Based Methods;Behavior-Based Systems;Probabilistic Inference",
    doi = "10.1109/LRA.2023.3342554"
}
        Sun et al., "MoML: Online Meta Adaptation for 3D Human Motion Prediction", CVPR, 2024. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Sun_MoML_2024_CVPR,
    author = "Sun, Xiaoning and Sun, Huaijiang and Li, Bin and Wei, Dong and Li, Weiqing and Lu, Jianfeng",
    title = "MoML: Online Meta Adaptation for 3D Human Motion Prediction",
    booktitle = "CVPR",
    year = "2024"
}
        Yu et al., "Pose-Transformed Equivariant Network for 3D Point Trajectory Prediction", CVPR, 2024. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Yu_Pose_2024_CVPR,
    author = "Yu, Ruixuan and Sun, Jian",
    title = "Pose-Transformed Equivariant Network for 3D Point Trajectory Prediction",
    booktitle = "CVPR",
    year = "2024"
}
        Chen et al., "Rethinking Human Motion Prediction with Symplectic Integral", CVPR, 2024. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Chen_Rethinking_2024_CVPR,
    author = "Chen, Haipeng and Lyu, Kedi and Liu, Zhenguang and Yin, Yifang and Yang, Xun and Lyu, Yingda",
    title = "Rethinking Human Motion Prediction with Symplectic Integral",
    booktitle = "CVPR",
    year = "2024"
}
        Jeong et al., "Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning", CVPR, 2024. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Jeong_Multi_2024_CVPR,
    author = "Jeong, Jaewoo and Park, Daehee and Yoon, Kuk-Jin",
    title = "Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning",
    booktitle = "CVPR",
    year = "2024"
}
        Gao et al., "Decompose More and Aggregate Better: Two Closer Looks at Frequency Representation Learning for Human Motion Prediction", CVPR, 2023. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Gao_2023_CVPR,
    author = "Gao, Xuehao and Du, Shaoyi and Wu, Yang and Yang, Yang",
    title = "Decompose More and Aggregate Better: Two Closer Looks at Frequency Representation Learning for Human Motion Prediction",
    booktitle = "CVPR",
    year = "2023"
}
        Peng et al., "Trajectory-Aware Body Interaction Transformer for Multi-Person Pose Forecasting", CVPR, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Peng_2023_CVPR,
    author = "Peng, Xiaogang and Mao, Siyuan and Wu, Zizhao",
    title = "Trajectory-Aware Body Interaction Transformer for Multi-Person Pose Forecasting",
    booktitle = "CVPR",
    year = "2023"
}
        Tanke et al., "Social Diffusion: Long-term Multiple Human Motion Anticipation", ICCV, 2023. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Tanke_2023_ICCV,
    author = "Tanke, Julian and Zhang, Linguang and Zhao, Amy and Tang, Chengcheng and Cai, Yujun and Wang, Lezi and Wu, Po-Chen and Gall, Juergen and Keskin, Cem",
    title = "Social Diffusion: Long-term Multiple Human Motion Anticipation",
    booktitle = "ICCV",
    year = "2023"
}
        Xu et al., "Joint-Relation Transformer for Multi-Person Motion Prediction", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Xu_2023_ICCV,
    author = "Xu, Qingyao and Mao, Weibo and Gong, Jingze and Xu, Chenxin and Chen, Siheng and Xie, Weidi and Zhang, Ya and Wang, Yanfeng",
    title = "Joint-Relation Transformer for Multi-Person Motion Prediction",
    booktitle = "ICCV",
    year = "2023"
}
        Chen et al., "HumanMAC: Masked Motion Completion for Human Motion Prediction", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Chen_2023_ICCV_1,
    author = "Chen, Ling-Hao and Zhang, JiaWei and Li, Yewen and Pang, Yiren and Xia, Xiaobo and Liu, Tongliang",
    title = "HumanMAC: Masked Motion Completion for Human Motion Prediction",
    booktitle = "ICCV",
    year = "2023"
}
        Xu et al., "Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Xu_2023_ICCV_1,
    author = "Xu, Chenxin and Tan, Robby T. and Tan, Yuhong and Chen, Siheng and Wang, Xinchao and Wang, Yanfeng",
    title = "Auxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction",
    booktitle = "ICCV",
    year = "2023"
}
        Ma et al., "Progressively Generating Better Initial Guesses Towards Next Stages for High-Quality Human Motion Prediction", CVPR, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Ma_2022_CVPR,
    author = "Ma, Tiezheng and Nie, Yongwei and Long, Chengjiang and Zhang, Qing and Li, Guiqing",
    title = "Progressively Generating Better Initial Guesses Towards Next Stages for High-Quality Human Motion Prediction",
    booktitle = "CVPR",
    year = "2022"
}
        Li et al., "Skeleton-Parted Graph Scattering Networks for 3D Human Motion Prediction", ECCV, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Li_2022_ECCV,
    author = "Li, Maosen and Chen, Siheng and Zhang, Zijing and Xie, Lingxi and Tian, Qi and Zhang, Ya",
    title = "Skeleton-Parted Graph Scattering Networks for {3D} Human Motion Prediction",
    booktitle = "ECCV",
    year = "2022"
}
        Sun et al., "Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction", ECCV, 2022. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Sun_2022_ECCV,
    author = "Sun, Xiaoning and Cui, Qiongjie and Sun, Huaijiang and Li, Bin and Li, Weiqing and Lu, Jianfeng",
    title = "Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction",
    booktitle = "ECCV",
    year = "2022"
}
        Wang et al., "Multi-Person 3D Motion Prediction with Multi-Range Transformers", NeurIPS, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Wang_2021_NeurIPS,
    author = "Wang, Jiashun and Xu, Huazhe and Narasimhan, Medhini and Wang, Xiaolong",
    booktitle = "NeurIPS",
    title = "Multi-Person {3D} Motion Prediction with Multi-Range Transformers",
    year = "2021"
}
        Cui et al., "Towards Accurate 3D Human Motion Prediction From Incomplete Observations", CVPR, 2021. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Cui_2021_CVPR,
    author = "Cui, Qiongjie and Sun, Huaijiang",
    title = "Towards Accurate {3D} Human Motion Prediction From Incomplete Observations",
    booktitle = "CVPR",
    year = "2021"
}
        Aliakbarian et al., "Contextually Plausible and Diverse 3D Human Motion Prediction", ICCV, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Aliakbarian_2021_ICCV,
    author = "Aliakbarian, Sadegh and Saleh, Fatemeh and Petersson, Lars and Gould, Stephen and Salzmann, Mathieu",
    title = "Contextually Plausible and Diverse {3D} Human Motion Prediction",
    booktitle = "ICCV",
    year = "2021"
}
        Dang et al., "MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction", ICCV, 2021. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Dang_2021_ICCV,
    author = "Dang, Lingwei and Nie, Yongwei and Long, Chengjiang and Zhang, Qing and Li, Guiqing",
    title = "{MSR-GCN}: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction",
    booktitle = "ICCV",
    year = "2021"
}
        Liu et al., "Motion Prediction Using Trajectory Cues", ICCV, 2021. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Liu_2021_ICCV,
    author = "Liu, Zhenguang and Su, Pengxiang and Wu, Shuang and Shen, Xuanjing and Chen, Haipeng and Hao, Yanbin and Wang, Meng",
    title = "Motion Prediction Using Trajectory Cues",
    booktitle = "ICCV",
    year = "2021"
}
        Li et al., "Directed Acyclic Graph Neural Network for Human Motion Prediction", ICRA, 2021. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Li_2021_ICRA,
    author = "Li, Qin and Chalvatzaki, Georgia and Peters, Jan and Wang, Yong",
    booktitle = "ICRA",
    title = "Directed Acyclic Graph Neural Network for Human Motion Prediction",
    year = "2021"
}
        Zhang et al., "Non-local Graph Convolutional Network for Joint Activity Recognition and Motion Prediction", IROS, 2021. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zhang_2021_IROS,
    author = "Zhang, Dianhao and Vien, Ngo Anh and Van, Mien and McLoone, Seán",
    booktitle = "IROS",
    title = "Non-local Graph Convolutional Network for Joint Activity Recognition and Motion Prediction",
    year = "2021"
}
        Aliakbarian et al., "A Stochastic Conditioning Scheme for Diverse Human Motion Prediction", CVPR, 2020. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Aliakbarian_2020_CVPR,
    author = "Aliakbarian, Sadegh and Saleh, Fatemeh Sadat and Salzmann, Mathieu and Petersson, Lars and Gould, Stephen",
    title = "A Stochastic Conditioning Scheme for Diverse Human Motion Prediction",
    booktitle = "CVPR",
    year = "2020"
}
        Cui et al., "Learning Dynamic Relationships for 3D Human Motion Prediction", CVPR, 2020. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Cui_2020_CVPR,
    author = "Cui, Qiongjie and Sun, Huaijiang and Yang, Fei",
    title = "Learning Dynamic Relationships for 3D Human Motion Prediction",
    booktitle = "CVPR",
    year = "2020"
}
        Li et al., "Dynamic Multiscale Graph Neural Networks for 3D Skeleton Based Human Motion Prediction", CVPR, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Li_2020_CVPR,
    author = "Li, Maosen and Chen, Siheng and Zhao, Yangheng and Zhang, Ya and Wang, Yanfeng and Tian, Qi",
    title = "Dynamic Multiscale Graph Neural Networks for {3D} Skeleton Based Human Motion Prediction",
    booktitle = "CVPR",
    year = "2020"
}
        Cai et al., "Learning Progressive Joint Propagation for Human Motion Prediction", ECCV, 2020. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Cai_2020_ECCV,
    author = "Cai, Yujun and Huang, Lin and Wang, Yiwei and Cham, Tat-Jen and Cai, Jianfei and Yuan, Junsong and Liu, Jun and Yang, Xu and Zhu, Yiheng and Shen, Xiaohui and Liu, Ding and Liu, Jing and Thalmann, Nadia M",
    title = "Learning Progressive Joint Propagation for Human Motion Prediction",
    booktitle = "ECCV",
    year = "2020"
}
        Chao et al., "Adversarial Refinement Network for Human Motion Prediction", ACCV, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Chao_2020_ACCV,
    author = "Chao, Xianjin and Bin, Yanrui and Chu, Wenqing and Cao, Xuan and Ge, Yanhao and Wang, Chengjie and Li, Jilin and Huang, Feiyue and Leung, Howard",
    title = "Adversarial Refinement Network for Human Motion Prediction",
    booktitle = "ACCV",
    year = "2020"
}
        Lebailly et al., "Motion Prediction Using Temporal Inception Module", ACCV, 2020. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Lebailly_2020_ACCV,
    author = "Lebailly, Tim and Kiciroglu, Sena and Salzmann, Mathieu and Fua, Pascal and Wang, Wei",
    title = "Motion Prediction Using Temporal Inception Module",
    booktitle = "ACCV",
    year = "2020"
}
        Mao et al., "Learning Trajectory Dependencies For Human Motion Prediction", ICCV, 2019. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Mao_2019_ICCV,
    author = "Mao, Wei and Liu, Miaomiao and Salzmann, Mathieu and Li, Hongdong",
    title = "Learning Trajectory Dependencies For Human Motion Prediction",
    booktitle = "ICCV",
    year = "2019"
}
      Bibtex 
      @Misc{CMU_Mocap_2016,
    author = "CMU",
    title = "{CMU} Graphics Lab Motion Capture Database",
    howpublished = "http://mocap.cs.cmu.edu/",
    year = "2016"
}
    CMU Panoptic link paper arxiv
    • Summary: A multiview group activity dataset recorded with 10 RGB-D sensors and 30+ HD views with the corresponding 3D annotations
    • Applications: Action prediction, Motion prediction
    • Data type and annotations: RGBD, multiview, 3D pose, 3D facial landmark, Transcripts
    • Task: Interaction
      Used in papers
        Joo et al., "Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction In A Triadic Interaction", CVPR, 2019. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Joo_2019_CVPR,
    author = "Joo, Hanbyul and Simon, Tomas and Cikara, Mina and Sheikh, Yaser",
    title = "Towards Social Artificial Intelligence: Nonverbal Social Signal Prediction In A Triadic Interaction",
    booktitle = "CVPR",
    year = "2019"
}
        Choudhury et al., "TEMPO: Efficient Multi-View Pose Estimation, Tracking, and Forecasting", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Choudhury_2023_ICCV,
    author = "Choudhury, Rohan and Kitani, Kris M. and Jeni, Laszlo A.",
    title = "TEMPO: Efficient Multi-View Pose Estimation, Tracking, and Forecasting",
    booktitle = "ICCV",
    year = "2023"
}
        Wang et al., "Multi-Person 3D Motion Prediction with Multi-Range Transformers", NeurIPS, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Wang_2021_NeurIPS,
    author = "Wang, Jiashun and Xu, Huazhe and Narasimhan, Medhini and Wang, Xiaolong",
    booktitle = "NeurIPS",
    title = "Multi-Person {3D} Motion Prediction with Multi-Range Transformers",
    year = "2021"
}
        Yasar et al., "A Scalable Approach to Predict Multi-Agent Motion for Human-Robot Collaboration", RAL, 2021. paper
          Datasets Metrics
          Bibtex 
          @Article{Yasar_2021_RAL,
    author = "Yasar, Mohammad Samin and Iqbal, Tariq",
    journal = "RAL",
    title = "A Scalable Approach to Predict Multi-Agent Motion for Human-Robot Collaboration",
    year = "2021",
    volume = "6",
    number = "2",
    pages = "1686-1693"
}
      Bibtex 
      @InProceedings{Joo_2015_ICCV_2,
    author = "Joo, Hanbyul and Liu, Hao and Tan, Lei and Gui, Lin and Nabbe, Bart and Matthews, Iain and Kanade, Takeo and Nobuhara, Shohei and Sheikh, Yaser",
    title = "Panoptic Studio: A Massively Multiview System For Social Motion Capture",
    booktitle = "ICCV",
    year = "2015"
}
    Cobots and Humans in Industrial COllaboration (CHICO) link paper arxiv
    • Summary: A dataset of multi-view videos, 3D poses and trajectories of 20 human operators and cobots, engaging in 7 realistic industrial actions.
    • Applications: Motion prediction
    • Data type and annotations: RGB, 3D Pose
    • Task: Object interaction
      Used in papers
        Mascaro et al., "Robot Interaction Behavior Generation based on Social Motion Forecasting for Human-Robot Interaction", ICRA, 2024. paper arxiv
          Datasets Metrics
          Bibtex 
          @inproceedings{Mascaro_Robot_2024_ICRA,
    author = "Mascaro, Esteve Valls and Yan, Yashuai and Lee, Dongheui",
    booktitle = "ICRA",
    title = "Robot Interaction Behavior Generation based on Social Motion Forecasting for Human-Robot Interaction",
    year = "2024"
}
        Sampieri et al., "Pose Forecasting in Industrial Human-Robot Collaboration", ECCV, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Sampieri_2022_ECCV,
    author = "Sampieri, Alessio and di Melendugno, Guido Maria D’Amely and Avogaro, Andrea and Cunico, Federico and Setti, Francesco and Skenderi, Geri and Cristani, Marco and Galasso, Fabio",
    title = "Pose Forecasting in Industrial Human-Robot Collaboration",
    booktitle = "ECCV",
    year = "2022"
}
      Bibtex 
      @InProceedings{Sampieri_2022_ECCV,
    author = "Sampieri, Alessio and di Melendugno, Guido Maria D’Amely and Avogaro, Andrea and Cunico, Federico and Setti, Francesco and Skenderi, Geri and Cristani, Marco and Galasso, Fabio",
    title = "Pose Forecasting in Industrial Human-Robot Collaboration",
    booktitle = "ECCV",
    year = "2022"
}
    Collaborative Action (CoAx) link paper
    • Summary: A dataset of human robot collaboration using a robot arm.
    • Applications: Other prediction
    • Data type and annotations: RGB, Depth, Activity label
    • Task: Human Robot Collaboration
      Used in papers
        Lagamtzis et al., "Exploiting Spatio-Temporal Human-Object Relations Using Graph Neural Networks for Human Action Recognition and 3D Motion Forecasting", IROS, 2023. paper
          Datasets Metrics
          Bibtex 
          @INPROCEEDINGS{Lagamtzis_2023_IROS,
    author = "Lagamtzis, Dimitrios and Schmidt, Fabian and Seyler, Jan and Dang, Thao and Schober, Steffen",
    booktitle = "IROS",
    title = "Exploiting Spatio-Temporal Human-Object Relations Using Graph Neural Networks for Human Action Recognition and 3D Motion Forecasting",
    year = "2023"
}
      Bibtex 
      @inproceedings{lagamtzis2022coax,
    author = "Lagamtzis, Dimitrios and Schmidt, Fabian and Seyler, Jan R and Dang, Thao",
    title = "CoAx: Collaborative Action Dataset for Human Motion Forecasting in an Industrial Workspace.",
    booktitle = "ICAART",
    year = "2022"
}
    Collective Activity (CA) link paper
    • Summary: A dataset of 40+ video clips showing collective activities including crossing, waiting, queueing, walking and talking
    • Applications: Action prediction, Trajectory prediction, Motion prediction
    • Data type and annotations: RGB, bounding box, attribute, activity label, temporal segment, pose
    • Task: Interaction
      Used in papers
        Chen et al., "Group Activity Prediction with Sequential Relational Anticipation Model", ECCV, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Chen_2020_ECCV,
    author = "Chen, Junwen and Bao, Wentao and Kong, Yu",
    title = "Group Activity Prediction with Sequential Relational Anticipation Model",
    booktitle = "ECCV",
    year = "2020"
}
        Yao et al., "Multiple Granularity Group Interaction Prediction", CVPR, 2018. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Yao_2018_CVPR,
    author = "Yao, Taiping and Wang, Minsi and Ni, Bingbing and Wei, Huawei and Yang, Xiaokang",
    title = "Multiple Granularity Group Interaction Prediction",
    booktitle = "CVPR",
    year = "2018"
}
      Bibtex 
      @InProceedings{Choi_2009_ICCVW,
    author = "Choi, Wongun and Shahid, Khuram and Savarese, Silvio",
    title = "What Are They Doing?: Collective Activity Classification Using Spatio-Temporal Relationship Among People",
    booktitle = "ICCVW",
    year = "2009"
}
    Collision Events for Video Representation and Reasoning (CLEVRER) link paper arxiv
    • Summary: A dataset of 10000 videos of 5s each generated using physics engine containing various shapes with different colors for evaluation of reasoning tasks.
    • Applications:
    • Data type and annotations: RGB, Q&A
    • Task: Object (simulation)
      Used in papers
        Chen et al., "Probabilistic Forecasting with Stochastic Interpolants and Follmer Processes", ICML, 2024. paper arxiv code
          Datasets Metrics
          Bibtex 
          @inproceedings{Chen_probabilistic_ICML,
    author = "Chen, Yifan and Goldstein, Mark and Hua, Mengjian and Albergo, Michael Samuel and Boffi, Nicholas Matthew and Vanden-Eijnden, Eric",
    title = "Probabilistic Forecasting with Stochastic Interpolants and Follmer Processes",
    booktitle = "ICML",
    year = "2024"
}
      Bibtex 
      @inproceedings{Yi_CLEVRER_2020_ICLR,
    author = "Yi*, Kexin and Gan*, Chuang and Li, Yunzhu and Kohli, Pushmeet and Wu, Jiajun and Torralba, Antonio and Tenenbaum, Joshua B.",
    title = "CLEVRER: Collision Events for Video Representation and Reasoning",
    booktitle = "ICLR",
    year = "2020"
}
    CoMaD link paper
    • Summary: A dataset of 3 collaborative tasks between a human and a robot with over 60 episodes of activities.
    • Applications:
    • Data type and annotations: RGB, Audio, Pose
    • Task: Interaction
      Used in papers
        Kedia et al., "ManiCast: Collaborative Manipulation with Cost-Aware Human Forecasting", CoRL, 2023. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Kushal_2023_CoRL,
    author = "Kedia, Kushal and Dan, Prithwish and Bhardwaj, Atiksh and Choudhury, Sanjiban",
    title = "ManiCast: Collaborative Manipulation with Cost-Aware Human Forecasting",
    booktitle = "CoRL",
    year = "2023"
}
      Bibtex 
      @InProceedings{Kushal_2023_CoRL,
    author = "Kedia, Kushal and Dan, Prithwish and Bhardwaj, Atiksh and Choudhury, Sanjiban",
    title = "ManiCast: Collaborative Manipulation with Cost-Aware Human Forecasting",
    booktitle = "CoRL",
    year = "2023"
}
    Composing Actions from Language and Vision (CALVIN) link paper arxiv
    • Summary: A dataset of a simulated robotic arm manipulating basic objects.
    • Applications: Video prediction
    • Data type and annotations: RGBD, State
    • Task: Simulation
      Used in papers
        Nematollahi et al., "T3VIP: Transformation-based $3\mathrmD$ Video Prediction", IROS, 2022. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Nematollahi_2022_IROS,
    author = "Nematollahi, Iman and Rosete-Beas, Erick and Azad, Seyed Mahdi B. and Rajan, Raghu and Hutter, Frank and Burgard, Wolfram",
    booktitle = "IROS",
    title = "{T3VIP}: Transformation-based $3\mathrm{D}$ Video Prediction",
    year = "2022"
}
      Bibtex 
      @Article{Mees_2022_RAL,
    author = "Mees, Oier and Hermann, Lukas and Rosete-Beas, Erick and Burgard, Wolfram",
    journal = "RAL",
    title = "{CALVIN}: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks",
    volume = "7",
    number = "3",
    pages = "7327-7334",
    year = "2022"
}
    COPILOT link paper arxiv
    • Summary: A dataset of 8.6M egocentric RGBD synthetic data with collision labels and heat maps.
    • Applications: Other prediction
    • Data type and annotations: RGBD, Collision region
    • Task: Simulation (Ego)
      Used in papers
        Pan et al., "COPILOT: Human-Environment Collision Prediction and Localization from Egocentric Videos", ICCV, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Pan_2023_ICCV,
    author = "Pan, Boxiao and Shen, Bokui and Rempe, Davis and Paschalidou, Despoina and Mo, Kaichun and Yang, Yanchao and Guibas, Leonidas J.",
    title = "COPILOT: Human-Environment Collision Prediction and Localization from Egocentric Videos",
    booktitle = "ICCV",
    year = "2023"
}
      Bibtex 
      @InProceedings{Pan_2023_ICCV,
    author = "Pan, Boxiao and Shen, Bokui and Rempe, Davis and Paschalidou, Despoina and Mo, Kaichun and Yang, Yanchao and Guibas, Leonidas J.",
    title = "COPILOT: Human-Environment Collision Prediction and Localization from Egocentric Videos",
    booktitle = "ICCV",
    year = "2023"
}
    CrowdNav link paper arxiv
    • Summary: A dataset of simulated pedestrian crowds crossing in a circular formation.
    • Applications: Trajectory prediction
    • Data type and annotations: Trajectory
    • Task: Simulation
      Used in papers
        Bagi et al., "Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting", ICML, 2023. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Bagi_2023_ICML,
    author = "Bagi, Shayan Shirahmad Gale and Gharaee, Zahra and Schulte, Oliver and Crowley, Mark",
    title = "Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting",
    booktitle = "ICML",
    year = "2023"
}
      Bibtex 
      @inproceedings{Chen_2019_ICRA,
    author = "Chen, Changan and Liu, Yuejiang and Kreiss, Sven and Alahi, Alexandre",
    title = "Crowd-robot interaction: Crowd-aware robot navigation with attention-based deep reinforcement learning",
    booktitle = "ICRA",
    year = "2019"
}
    CUHK Avenue link paper
    • Summary: A dataset of 37 video clips with 30K+ frames showing abnormal events
    • Applications: Video prediction, Trajectory prediction
    • Data type and annotations: RGB, bounding box, anomaly, temporal segment
    • Task: Surveillance, Anomaly
      Used in papers
        Kwon et al., "Predicting Future Frames Using Retrospective Cycle GAN", CVPR, 2019. paper
        Cao et al., "A New Comprehensive Benchmark for Semi-Supervised Video Anomaly Detection and Anticipation", CVPR, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Cao_2023_CVPR,
    author = "Cao, Congqi and Lu, Yue and Wang, Peng and Zhang, Yanning",
    title = "A New Comprehensive Benchmark for Semi-Supervised Video Anomaly Detection and Anticipation",
    booktitle = "CVPR",
    year = "2023"
}
        Xu et al., "Encoding Crowd Interaction With Deep Neural Network For Pedestrian Trajectory Prediction", CVPR, 2018. paper code
          Datasets Metrics
          Bibtex 
          @InProceedings{Xu_2018_CVPR_encoding,
    author = "Xu, Yanyu and Piao, Zhixin and Gao, Shenghua",
    title = "Encoding Crowd Interaction With Deep Neural Network For Pedestrian Trajectory Prediction",
    booktitle = "CVPR",
    year = "2018"
}
      Bibtex 
      @InProceedings{Lu_2013_ICCV,
    author = "Lu, Cewu and Shi, Jianping and Jia, Jiaya",
    title = "Abnormal Event Detection At 150 Fps In {M}atlab",
    booktitle = "ICCV",
    year = "2013"
}
    DADA-2000 link paper
    • Summary: A dataset of driving scenarios with collected driver's gaze.
    • Applications: Action prediction
    • Data type and annotations: RGB, Gaze
    • Task: Driving
      Used in papers
        Bao et al., "DRIVE: Deep Reinforced Accident Anticipation With Visual Explanation", ICCV, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Bao_2021_ICCV,
    author = "Bao, Wentao and Yu, Qi and Kong, Yu",
    title = "{DRIVE}: Deep Reinforced Accident Anticipation With Visual Explanation",
    booktitle = "ICCV",
    year = "2021"
}
      Bibtex 
      @ARTICLE{FANG_2021_TITS,
    author = "Fang, J. and Yan, D. and Qiao, J. and Xue, J. and Yu, H.",
    journal = "Trans-ITS",
    title = "{DADA}: Driver Attention Prediction in Driving Accident Scenarios",
    year = "2021"
}
    Daimler link paper
    • Summary: A grayscale dataset of 70K+ pedestrian samples recorded during the course of 27 minutes of driving
    • Applications: Action prediction
    • Data type and annotations: Grayscale, bounding box
    • Task: Driving
      Used in papers
        Hariyono et al., "Estimation Of Collision Risk For Improving Driver's Safety", IECON, 2016. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Hariyono_2016_IES,
    author = "Hariyono, Joko and Shahbaz, Ajmal and Kurnianggoro, Laksono and Jo, Kang-Hyun",
    title = "Estimation Of Collision Risk For Improving Driver's Safety",
    booktitle = "IECON",
    year = "2016"
}
      Bibtex 
      @Article{Enzweiler_2008_PAMI,
    author = "Enzweiler, Markus and Gavrila, Dariu M",
    title = "Monocular Pedestrian Detection: Survey And Experiments",
    journal = "PAMI",
    volume = "31",
    number = "12",
    pages = "2179--2195",
    year = "2008"
}
    Daimler Path link paper
    • Summary: A dataset of 68 pedestrian sequences recorded using a dashboard camera inside a vehicle during stationary and mobile states
    • Applications: Action prediction
    • Data type and annotations: Stereo grayscale, bounding box, temporal segment, vehicle sensors
    • Task: Driving
      Used in papers
        Schulz et al., "Pedestrian Intention Recognition Using Latent-Dynamic Conditional Random Fields", IV, 2015. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Schulz_2015_IV,
    author = "Schulz, Andreas Th and Stiefelhagen, Rainer",
    title = "Pedestrian Intention Recognition Using Latent-Dynamic Conditional Random Fields",
    booktitle = "IV",
    year = "2015"
}
        Schulz et al., "A Controlled Interactive Multiple Model Filter For Combined Pedestrian Intention Recognition And Path Prediction", ITSC, 2015. paper
          Datasets Metrics
          Bibtex 
          @InProceedings{Schulz_2015_ITSC,
    author = "Schulz, Andreas and Stiefelhagen, Rainer",
    title = "A Controlled Interactive Multiple Model Filter For Combined Pedestrian Intention Recognition And Path Prediction",
    booktitle = "ITSC",
    year = "2015"
}
      Bibtex 
      @InProceedings{Schneider_2013_GCPR,
    author = "Schneider, Nicolas and Gavrila, Dariu M",
    title = "Pedestrian Path Prediction With Recursive Bayesian Filters: A Comparative Study",
    booktitle = "GCPR",
    year = "2013"
}
    Dancing link paper arxiv
    • Summary: A dataset of body poses of single dancers
    • Applications: Video prediction
    • Data type and annotations: RGB
    • Task: Activity
      Used in papers
        Lee et al., "Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction", ICLR, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Wonkwang_2021_ICLR,
    author = "Lee, Wonkwang and Jung, Whie and Zhang, Han and Chen, Ting and Koh, Jing Yu and Huang, Thomas and Yoon, Hyungsuk and Lee, Honglak and Hong, Seunghoon",
    booktitle = "ICLR",
    title = "Revisiting Hierarchical Approach for Persistent Long-Term Video Prediction",
    year = "2021"
}
      Bibtex 
      @InProceedings{Ting_2018_NeurIPS,
    author = "Wang, Ting-Chun and Liu, Ming-Yu and Zhu, Jun-Yan and Liu, Guilin and Tao, Andrew and Kautz, Jan and Catanzaro, Bryan",
    booktitle = "NeurIPS",
    title = "Video-to-Video Synthesis",
    year = "2018"
}
    Dashcam Accident Dataset (DAD) link paper
    • Summary: A dataset of 620 video sequences of traffic accidents recorded in six cities
    • Applications: Action prediction
    • Data type and annotations: RGB, bounding box, object class, temporal segment, Tracking ID
    • Task: Driving
      Used in papers
        Bao et al., "DRIVE: Deep Reinforced Accident Anticipation With Visual Explanation", ICCV, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Bao_2021_ICCV,
    author = "Bao, Wentao and Yu, Qi and Kong, Yu",
    title = "{DRIVE}: Deep Reinforced Accident Anticipation With Visual Explanation",
    booktitle = "ICCV",
    year = "2021"
}
        Suzuki et al., "Anticipating Traffic Accidents With Adaptive Loss And Large-Scale Incident Db", CVPR, 2018. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Suzuki_2018_CVPR,
    author = "Suzuki, Tomoyuki and Kataoka, Hirokatsu and Aoki, Yoshimitsu and Satoh, Yutaka",
    title = "Anticipating Traffic Accidents With Adaptive Loss And Large-Scale Incident Db",
    booktitle = "CVPR",
    year = "2018"
}
        Zeng et al., "Agent-Centric Risk Assessment: Accident Anticipation And Risky Region Localization", CVPR, 2017. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Zeng_2017_CVPR,
    author = "Zeng, Kuo-Hao and Chou, Shih-Han and Chan, Fu-Hsiang and Carlos Niebles, Juan and Sun, Min",
    title = "Agent-Centric Risk Assessment: Accident Anticipation And Risky Region Localization",
    booktitle = "CVPR",
    year = "2017"
}
        Yao et al., "Unsupervised Traffic Accident Detection in First-Person Videos", IROS, 2019. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Yao_2019_IROS,
    author = "Yao, Y. and Xu, M. and Wang, Y. and Crandall, D. J. and Atkins, E. M.",
    booktitle = "IROS",
    title = "Unsupervised Traffic Accident Detection in First-Person Videos",
    year = "2019"
}
      Bibtex 
      @InProceedings{Chan_2017_ACCV,
    author = "Chan, Fu-Hsiang and Chen, Yu-Ting and Xiang, Yu and Sun, Min",
    editor = "Lai, Shang-Hong and Lepetit, Vincent and Nishino, Ko and Sato, Yoichi",
    title = "Anticipating Accidents In Dashcam Videos",
    booktitle = "ACCV",
    year = "2017"
}
    DAVIS17 link arxiv
    • Summary: A dataset consisting of 150 video sequences with over 10K frames and 376 objects with associated segmentation masks.
    • Applications: Video prediction
    • Data type and annotations: RGB, Segmentation
    • Task: Activity
      Used in papers
        Hu et al., "A Dynamic Multi-Scale Voxel Flow Network for Video Prediction", CVPR, 2023. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Hu_2023_CVPR,
    author = "Hu, Xiaotao and Huang, Zhewei and Huang, Ailin and Xu, Jun and Zhou, Shuchang",
    title = "A Dynamic Multi-Scale Voxel Flow Network for Video Prediction",
    booktitle = "CVPR",
    year = "2023"
}
      Bibtex 
      @article{Pont_2017_Arxiv,
    author = "Pont-Tuset, Jordi and Perazzi, Federico and Caelles, Sergi and Arbelaez, Pablo and Sorkine-Hornung, Alex and Van Gool, Luc",
    title = "The 2017 davis challenge on video object segmentation",
    journal = "arXiv:1704.00675",
    year = "2017"
}
    Deformable Rigid Interaction Prediction (DRIP) link paper arxiv
    • Summary: A dataset of simulated deformable and rigid objects with associated graph representation.
    • Applications: Other prediction
    • Data type and annotations: RGB, Graph
    • Task: Object (simulation)
      Used in papers
        Weng et al., "Graph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects", IROS, 2021. paper arxiv code
          Datasets Metrics
          Bibtex 
          @InProceedings{Weng_2021_IROS,
    author = "Weng, Zehang and Paus, Fabian and Varava, Anastasiia and Yin, Hang and Asfour, Tamim and Kragic, Danica",
    booktitle = "IROS",
    title = "Graph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects",
    year = "2021"
}
      Bibtex 
      @InProceedings{Weng_2021_IROS,
    author = "Weng, Zehang and Paus, Fabian and Varava, Anastasiia and Yin, Hang and Asfour, Tamim and Kragic, Danica",
    booktitle = "IROS",
    title = "Graph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects",
    year = "2021"
}
    DFAUST link paper
    • Summary: A dataset of 3D poses recorded over time (3D) at 60 fps
    • Applications: Motion prediction
    • Data type and annotations: 3D Pose
    • Task: Activity
      Used in papers
        Yuan et al., "3DMotion-Net: Learning Continuous Flow Function for 3D Motion Prediction", IROS, 2020. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{Yuan_2020_IROS,
    author = "Yuan, S. and Li, X. and Tzes, A. and Fang, Y.",
    booktitle = "IROS",
    title = "{3DMotion-Net}: Learning Continuous Flow Function for {3D} Motion Prediction",
    year = "2020"
}
      Bibtex 
      @InProceedings{Bogo_2017_CVPR,
    author = "Bogo, Federica and Romero, Javier and Pons-Moll, Gerard and Black, Michael J.",
    title = "Dynamic {FAUST}: Registering Human Bodies in Motion",
    booktitle = "CVPR",
    year = "2017"
}
    DIPLECS link paper
    • Summary: A dataset of 3.5 hours of driving with the corresponding steering angle computed based on a marker on the steering wheel
    • Applications: Other prediction
    • Data type and annotations: RGB, vehicle sensors
    • Task: Driving
      Used in papers
        He et al., "Aggregated Sparse Attention For Steering Angle Prediction", ICPR, 2018. paper arxiv
          Datasets Metrics
          Bibtex 
          @InProceedings{He_2018_ICPR,
    author = "He, S. and Kangin, D. and Mi, Y. and Pugeault, N.",
    booktitle = "ICPR",
    title = "Aggregated Sparse Attention For Steering Angle Prediction",
    year = "2018"
}
      Bibtex 
      @InProceedings{Pugeault_2010_ECCV,
    author = "Pugeault, Nicolas and Bowden, Richard",
    title = "Learning Pre-Attentive Driving Behaviour From Holistic Visual Features",
    booktitle = "ECCV",
    year = "2010"
}
    DUT link paper arxiv
    • Summary: A dataset of vehicles and pedestrians recorded at shared spaces with over 1.7K pedestrian trajectories divided in 28 clips.
    • Applications:
    • Data type and annotations: RGB, Trajectory
    • Task: Driving
      Used in papers
        Anderson et al., "Off the Beaten Sidewalk: Pedestrian Prediction in Shared Spaces for Autonomous Vehicles", RAL, 2020. paper
          Datasets Metrics
          Bibtex 
          @ARTICLE{Anderson_Off_2020_RAL,
    author = "Anderson, Cyrus and Vasudevan, Ram and Johnson-Roberson, Matthew",
    journal = "RAL",
    title = "Off the Beaten Sidewalk: Pedestrian Prediction in Shared Spaces for Autonomous Vehicles",
    year = "2020",
    volume = "5",
    number = "4",
    pages = "6892-6899"
}
      Bibtex 
      @inproceedings{Yang_Top_2019_IV,
    author = "Yang, Dongfang and Li, Linhui and Redmill, Keith and Özgüner, Ümit",
    booktitle = "IV",
    title = "Top-view Trajectories: A Pedestrian Dataset of Vehicle-Crowd Interaction from Controlled Experiments and Crowded Campus",
    year = "2019"
}