[NeurIPS 2023] MotionGPT: Human Motion as a Foreign Language, a unified motion-language generation model using LLMs
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Updated
Apr 3, 2024 - Python
[NeurIPS 2023] MotionGPT: Human Motion as a Foreign Language, a unified motion-language generation model using LLMs
[SIGGRAPH 2022 Journal Track] AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars
MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model
Official implementation of "MoMask: Generative Masked Modeling of 3D Human Motions (CVPR2024)"
HumanML3D: A large and diverse 3d human motion-language dataset.
(CVPR 2023) Pytorch implementation of “T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations”
[CVPR 2023] Executing your Commands via Motion Diffusion in Latent Space, a fast and high-quality motion diffusion model
Official implementation for "Generating Diverse and Natural 3D Human Motions from Texts (CVPR2022)."
Official PyTorch implementation of the paper "TEMOS: Generating diverse human motions from textual descriptions", ECCV 2022 (Oral)
[CVPR 2022] PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision (Oral)
[ICML 2024] 🍅HumanTOMATO: Text-aligned Whole-body Motion Generation
[ICCV-2023] Official code for work "HumanMAC: Masked Motion Completion for Human Motion Prediction".
List of recent advances for human avatars, including generation, reconstruction, and editing, etc.
[IJCV 2024] InterGen: Diffusion-based Multi-human Motion Generation under Complex Interactions
[CVPR 2024] Official Implementation of "Seamless Human Motion Composition with Blended Positional Encodings".
The official PyTorch implementation of the paper "MotionGPT: Finetuned LLMs are General-Purpose Motion Generators"
Official implementations for "Action2Motion: Conditioned Generation of 3D Human Motions (ACM MultiMedia 2020)"
[Open-source Project] UniMoCap: community implementation to unify the text-motion datasets (HumanML3D, KIT-ML, and BABEL) and whole-body motion dataset (Motion-X).
This is an open collection of state-of-the-art (SOTA), novel Text to X (X can be everything) methods (papers, codes and datasets).
Official implementation of the NeurIPS22 paper "HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes"
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