HumanML3D Dataset
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HumanML3D is a 3D human motion-language dataset that originates from a combination of HumanAct12 and Amass dataset. It covers a broad range of human actions such as daily activities (e.g., 'walking', 'jumping'), sports (e.g., 'swimming', 'playing golf'), acrobatics (e.g., 'cartwheel') and artistry (e.g., 'dancing'). Overall, HumanML3D dataset consists of 14,616 motions and 44,970 descriptions composed by 5,371 distinct words. The total length of motions amounts to 28.59 hours. The average motion length is 7.1 seconds, while average description length is 12 words.
PDF) DiverseMotion: Towards Diverse Human Motion Generation via Discrete Diffusion
BABEL Dataset Papers With Code
Motion Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM
RealTimeData/arxiv_july_week1_2023 · Datasets at Hugging Face
PDF) MoFusion: A Framework for Denoising-Diffusion-based Motion Synthesis
GitHub - GuyTevet/motion-diffusion-model: The official PyTorch impleme
Generate Movement from Text Descriptions with T2M-GPT - Voxel51
GitHub - EricGuo5513/text-to-motion: Official implementation for Generating Diverse and Natural 3D Human Motions from Texts (CVPR2022).
Ling-Hao CHEN's Homepage
MDM:Human Motion Diffusion Model - 知乎
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