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HumanML3D Dataset

$ 12.99

4.8 (305) In stock

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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