https://github.com/JingLi513/Audio2Gestures

Audio2Motion Official implementation for Audio2Motion: Generating Diverse Gestures from Speech with Conditional Variational Autoencoders.
https://github.com/JingLi513/Audio2Gestures

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Audio2Motion Official implementation for Audio2Motion: Generating Diverse Gestures from Speech with Conditional Variational Autoencoders.

• Host: GitHub
• URL: https://github.com/JingLi513/Audio2Gestures
• Owner: JingLi513
• Created: 2021-08-06T14:56:09.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2024-01-01T23:52:33.000Z (9 months ago)
• Last Synced: 2024-04-23T20:34:40.551Z (5 months ago)
• Language: Python
• Size: 21.3 MB
• Stars: 116
• Watchers: 2
• Forks: 9
• Open Issues: 14
• Metadata Files:
  • Readme: README.md

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README

        
# Audio2Gestures

Official implementation for Audio2Gestures: Generating Diverse Gestures from Speech Audio with Conditional Variational Autoencoders， ICCV

## Dependencies

- [pytorch](https://pytorch.org/)

- [numpy](https://numpy.org/)

- [librosa](https://librosa.org/)

- [fbx](https://www.autodesk.com/developer-network/platform-technologies/fbx-sdk-2020-0)

- [smplx 1.0](https://github.com/vchoutas/smplx)

## Data Processing

1. Download fbx format data from [Trinity speech gesture](https://trinityspeechgesture.scss.tcd.ie/).

2. Retarget the data into SMPLX model using maya.

3. convert the fbx data to hdf5 format using script ``fbx2hdf.py``

## Training and testing

Run script ``bash start.sh``

## Visualizing

Run script ``python .\smplx2fbx.py --smplx .\for_smplx_retargeting.h5  --key LclRotation --fps 30  --synthesized .\input.h5 --fbx output.fbx`` 

## Reference

If you find our code useful for your research, please cite our paper.

> @inproceedings{li2021audio2gestures,  

>  title={Audio2Gestures: Generating Diverse Gestures from Speech Audio with Conditional Variational Autoencoders},  

>  author={Li, Jing and Kang, Di and Pei, Wenjie and Zhe, Xuefei and Zhang, Ying and He, Zhenyu and Bao, Linchao},  

>  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},  

>  pages={11293--11302},  

>  year={2021}  

> }