- Image Classification
- Action Classification
- Object Detection
- Image Segmentation
- Image Super Resolution
- Face Recognition
- 3D Reconstruction
- Diffusion
- Meta Learning
- Domain Generalization
- Semi Supervised Learning
- Data Augmentation
- Natural Language Processing
- Computer System for AI
- Util
Year | Name | Paper | Code |
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1998 | LeNet: Gradient-based learning applied to document recognition | ||
2012 | AlexNet: ImageNet Classification with Deep Convolutional Neural Networks | ||
2014 | VGGNet: Very Deep Convolutional Networks for Large-Scale Image Recognition | ||
2015 | GoogLeNet: Going Deeper with Convolutions | ||
2016 | ResNet: Deep Residual Learning for Image Recognition | ||
2017 | SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size | ||
2017 | DenseNet: Densely Connected Convolutional Networks | ||
2017 | XceptionNet: Deep Learning with Depthwise Separable Convolutions | ||
2018 | MobileNetV1: Efficient Convolutional Neural Networks for Mobile Vision Application | ||
2018 | ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices | ||
2018 | MobileNetV2: Inverted Residuals and Linear Bottlenecks | ||
2018 | NASNet: Learning Transferable Architectures for Scalable Image Recognition | ||
2018 | Squeeze Excitation Network: Squeeze-and-Excitation Networks | ||
2018 | Residual Attention Network: Residual Attention Network for Image Classification | ||
2019 | CBAM: Convolutional Block Attention Module | ||
2019 | MobileNetV3: Searching for MobileNetV3 | ||
2020 | RegeNet: Designing Network Design Spaces | ||
2021 | EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks | ||
2021 | Vision Transformer: An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale | ||
2021 | DeiT: Training data-efficient image transformers & distillation through attention | ||
2021 | Swin Transformer: Hierarchical Vision Transformer using Shifted Windows | ||
2012 | Pyramid vision transformer: A versatile backbone for dense prediction without convolutions | ||
2022 | ConvNeXt: A ConvNet for the 2020s | ||
2023 | ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders |
Year | Name | Paper | Code |
---|---|---|---|
2018 | Non-local Neural Networks |
Year | Name | Paper | Code |
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2013 | R-CNN: Rich feature hierarchies for accurate object detection and semantic segmentation | ||
2015 | Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks | ||
2016 | OHEM: Training Region-based Object Detectors with Online Hard Example Mining | ||
2016 | YOLOv1: You Only Look Once: Unified, Real-Time Object Detection | ||
2016 | SSD(Single Shot Detection): Single Shot MultiBox Detector | ||
2017 | FPN(Feature Pyramids Network): Feature Pyramid Networks for Object Detection | ||
2017 | RetinaNet: Focal loss for dense object detection | ||
2017 | Mask-RCNN: Mask R-CNN | ||
2018 | YOLOv3: An Incremental Improvement | ||
2018 | RefineDet: Single-Shot Refinement Neural Network for Object Detection | ||
2018 | M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network | ||
2019 | Mask scoring r-cnn | ||
2019 | FSFA: Feature selective anchor-free module for single-shot object detection | ||
2019 | Scratchdet: Exploring to train single-shot object detectors from scratch |
Year | Name | Paper | Code |
---|---|---|---|
2015 | U-Net: Convolutional Networks for Biomedical Image Segmentation | ||
2021 | TransUnet: Transformers make Strong Encoders for Medical Image Segmentation | ||
2021 | Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation | ||
2021 | UNETR: Transformers for 3D Medical Image Segmentation | ||
2023 | Medical Image Segmentation via Cascaded Attetnion Decoding |
Year | Name | Paper | Code |
---|---|---|---|
2014 | SRCNN: Image Super-Resolution Using Deep Convolutional Networks | ||
2016 | Pixel Shuffle: Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network | ||
2017 | Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial |
Year | Name | Paper | Code |
---|---|---|---|
2015 | FaceNet: A Unified Embedding for Face Recognition and Clustering | ||
2018 | SphereFace: Deep Hypersphere Embedding for Face Recognition | ||
2018 | CosFace: Large Margin Cosine Loss for Deep Face Recognition | ||
2018 | ArcFace: Additive Angular Margin Loss for Deep Face Recognition |
Year | Name | Paper | Code |
---|---|---|---|
2020 | NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis |
Year | Name | Paper | Code |
---|---|---|---|
2020 | Denoising Diffusion Probabilistic Models |
Year | Name | Paper | Code |
---|---|---|---|
2015 | SiameseNet: Siamese Neural Networks for One-shot Image Recognition | ||
2016 | MatchingNet: Matching Networks for One Shot Learning | ||
2017 | ProtoNet : Prototypical Networks for Few-shot Learning | ||
2017 | RelationNet : Learning to Compare: Relation Network for Few-Shot Learning |
Year | Name | Paper | Code |
---|---|---|---|
2016 | One-shot Learning with Memory-Augmented Neural Networks | ||
2017 | Meta Networks |
Year | Name | Paper | Code |
---|---|---|---|
2021 | Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification |
Year | Name | Paper | Code |
---|---|---|---|
2020 | Noisy Student: Self-training with Noisy Student improves ImageNet classification | ||
2021 | Meta Pseudo Labels |
Year | Name | Paper | Code |
---|---|---|---|
2018 | Mixup: Beyond Empirical Risk Minimization | ||
2019 | Cutmix: Regularization Strategy to Train Strong Classifiers with Localizable Features | ||
2019 | AutoAugment: Learning Augmentation Strategies from Data | - | |
2019 | RandAugment: Practical automated data augmentation with a reduced search space | - |
Year | Name | Paper | Code |
---|---|---|---|
2013 | CBoW & skip-gram: Efficient Estimation of Word Representations in Vector Space | ||
2017 | Transformer: Attention Is All You Need |
Year | Name | Paper | Code |
---|---|---|---|
2016 | Perceptron Learning for Reuse Prediction | ||
2018 | The Case for Learned Index Structures | ||
2019 | Improving Parallelism of Breadth First Search (BFS) Algorithm for Accelerated Performance on GPUs | ||
2020 | An Imitation Learning Approach for Cache Replacement | ||
2020 | ALEX: An Updatable Adaptive Learned Index | ||
2021 | FlashNeuron: SSD-Enabled Large-Batch Training of Very Deep Neural Networks | ||
2023 | EnvPipe: Performance-preserving DNN Training Framework for Saving Energy | ||
2023 | FLASH: Towards a High-performance Hardware Acceleration Architecture for Cross-silo Federated Learning |
Year | Name | Paper | Code |
---|---|---|---|
2017 | Temperature Scaling: On Calibration of Modern Neural Networks | ||
2020 | Label Smoothing: When Does Label Smoothing Help | - |