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README

MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model

<a href='https://scholar.google.com/citations?user=2QLD4fAAAAAJ&hl=en' target='_blank'>Mingyuan Zhang</a><sup>1</sup>*&emsp;
<a href='https://caizhongang.github.io/' target='_blank'>Zhongang Cai</a><sup>1,2</sup>*&emsp;
<a href='https://scholar.google.com/citations?user=lSDISOcAAAAJ&hl=zh-CN' target='_blank'>Liang Pan</a><sup>1</sup>&emsp;
<a href='https://hongfz16.github.io/' target='_blank'>Fangzhou Hong</a><sup>1</sup>&emsp;
<a href='https://gxyes.github.io/' target='_blank'>Xinying Guo</a><sup>1</sup>&emsp;
<a href='https://yanglei.me/' target='_blank'>Lei Yang</a><sup>2</sup>&emsp;
<a href='https://liuziwei7.github.io/' target='_blank'>Ziwei Liu</a><sup>1+</sup>






<sup>1</sup>S-Lab, Nanyang Technological University&emsp;
<sup>2</sup>SenseTime Research&emsp;






*equal contribution&emsp;
<sup>+</sup>corresponding author
play the guitar walk sadly walk happily check time

This repository contains the official implementation of MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model.


[Project Page][arXiv][Video][Colab Demo][Hugging Face Demo]

Updates

[10/2022] Add a 🤗Hugging Face Demo for text-driven motion generation!

[10/2022] Add a Colab Demo for text-driven motion generation! Open In Colab

[10/2022] Code release for text-driven motion generation!

[8/2022] Paper uploaded to arXiv. arXiv

Text-driven Motion Generation

You may refer to this file for detailed introduction.

Citation

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}
}

Acknowledgements

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).

Core symbols most depended-on inside this repo

to
called by 42
text2motion/trainers/ddpm_trainer.py
_extract_into_tensor
called by 25
text2motion/models/gaussian_diffusion.py
load
called by 18
text2motion/trainers/ddpm_trainer.py
save
called by 12
text2motion/trainers/ddpm_trainer.py
qrot_np
called by 10
text2motion/utils/quaternion.py
qmul_np
called by 8
text2motion/utils/quaternion.py
mean_flat
called by 6
text2motion/models/gaussian_diffusion.py
qinv_np
called by 5
text2motion/utils/quaternion.py

Shape

Method 137
Function 94
Class 40

Languages

Python100%

Modules by API surface

text2motion/models/gaussian_diffusion.py50 symbols
text2motion/datasets/evaluator_models.py40 symbols
text2motion/models/transformer.py32 symbols
text2motion/utils/quaternion.py24 symbols
text2motion/datasets/evaluator.py22 symbols
text2motion/trainers/ddpm_trainer.py16 symbols
text2motion/utils/skeleton.py14 symbols
text2motion/utils/utils.py13 symbols
text2motion/utils/motion_process.py10 symbols
text2motion/utils/metrics.py8 symbols
text2motion/tools/evaluation.py7 symbols
text2motion/datasets/dataset.py6 symbols

For agents

$ claude mcp add MotionDiffuse \
  -- python -m otcore.mcp_server <graph>

⬇ download graph artifact