(CVPR 2023) Pytorch implementation of “T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations”
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Updated
Sep 17, 2024 - Python
(CVPR 2023) Pytorch implementation of “T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations”
Official implementation of CVPR24 highlight paper "Move as You Say, Interact as You Can: Language-guided Human Motion Generation with Scene Affordance"
Official implementation of "MoMask: Generative Masked Modeling of 3D Human Motions (CVPR2024)"
[CVPR 2022] OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object Interaction
Official implementation of "TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts (ECCV2022)"
Official implementation for "Generating Diverse and Natural 3D Human Motions from Texts (CVPR2022)."
HumanML3D: A large and diverse 3d human motion-language dataset.
Official implementations for "Action2Motion: Conditioned Generation of 3D Human Motions (ACM MultiMedia 2020)"
[CVPRW 2024] Official Implementation of "in2IN: Leveraging individual Information to Generate Human INteractions".
[IJCV 2024] InterGen: Diffusion-based Multi-human Motion Generation under Complex Interactions
MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model
Pytorch implementation of MoLA
[ECCV 2024] Official PyTorch implement of paper "ParCo: Part-Coordinating Text-to-Motion Synthesis": http://arxiv.org/abs/2403.18512
[ICML 2024] 🍅HumanTOMATO: Text-aligned Whole-body Motion Generation
[CVPR 2024] Official Implementation of "Seamless Human Motion Composition with Blended Positional Encodings".
[ICCV-2023] Official code for work "HumanMAC: Masked Motion Completion for Human Motion Prediction".
🕹️ Official Implementation of Conditional Motion In-betweening (CMIB) 🏃
[NeurIPS 2023] MotionGPT: Human Motion as a Foreign Language, a unified motion-language generation model using LLMs
Official PyTorch implementation of the paper "SINC: Spatial Composition of 3D Human Motions for Simultaneous Action Generation"
MotionDiffuseDCT: Investigating Dynamical Representations for Human Motion Generation
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