# Install the requirements using `virtualenv`:
cd $PWD/STAF
source scripts/install_pip.sh
You can download the required data and the pre-trained STAF model from here. You need to unzip the contents and the data directory structure should follow the below hierarchy.
${ROOT}
|-- data
| |-- base_data
We have prepared a demo code to run STAF on arbitrary videos. To do this you can just run:
python demo.py --vid_file demo_video.mp4 --gpu 0
Please refer to training issue and evaluation issue.
Part of the code is borrowed from the following projects, including PyMAF, MPS-Net. Many thanks to their contributions. Special thanks to camenduru for Colab Demo!
If you find this repository useful, please consider citing our paper and lightning the star:
@ARTICLE{yao2024staf,
author={Yao, Wei and Zhang, Hongwen and Sun, Yunlian and Tang, Jinhui},
journal={IEEE Transactions on Circuits and Systems for Video Technology},
title={STAF: 3D Human Mesh Recovery from Video with Spatio-Temporal Alignment Fusion},
year={2024},
volume={},
number={},
pages={1-1},
keywords={Hidden Markov models;Three-dimensional displays;Feature extraction;Image reconstruction;Solid modeling;Biological system modeling;Coherence;3D human mesh recovery;temporal coherence;feature pyramid;attention model},
doi={10.1109/TCSVT.2024.3410400}}