<a href='https://scholar.google.com/citations?user=2QLD4fAAAAAJ&hl=en' target='_blank'>Mingyuan Zhang</a><sup>1</sup>* 
<a href='https://caizhongang.github.io/' target='_blank'>Zhongang Cai</a><sup>1,2</sup>* 
<a href='https://scholar.google.com/citations?user=lSDISOcAAAAJ&hl=zh-CN' target='_blank'>Liang Pan</a><sup>1</sup> 
<a href='https://hongfz16.github.io/' target='_blank'>Fangzhou Hong</a><sup>1</sup> 
<a href='https://gxyes.github.io/' target='_blank'>Xinying Guo</a><sup>1</sup> 
<a href='https://yanglei.me/' target='_blank'>Lei Yang</a><sup>2</sup> 
<a href='https://liuziwei7.github.io/' target='_blank'>Ziwei Liu</a><sup>1+</sup>
<sup>1</sup>S-Lab, Nanyang Technological University 
<sup>2</sup>SenseTime Research 
*equal contribution 
<sup>+</sup>corresponding author
| play the guitar | walk sadly | walk happily | check time |
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This repository contains the official implementation of MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model.
[10/2022] Add a 🤗Hugging Face Demo for text-driven motion generation!
[10/2022] Add a Colab Demo for text-driven motion generation!
[10/2022] Code release for text-driven motion generation!
[8/2022] Paper uploaded to arXiv.
You may refer to this file for detailed introduction.
If you find our work useful for your research, please consider citing the paper:
@article{zhang2022motiondiffuse,
title={MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model},
author={Zhang, Mingyuan and Cai, Zhongang and Pan, Liang and Hong, Fangzhou and Guo, Xinying and Yang, Lei and Liu, Ziwei},
journal={arXiv preprint arXiv:2208.15001},
year={2022}
}
This study is supported by NTU NAP, MOE AcRF Tier 2 (T2EP20221-0033), and under the RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) Funding Initiative, as well as cash and in-kind contribution from the industry partner(s).
$ claude mcp add MotionDiffuse \
-- python -m otcore.mcp_server <graph>