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STAF: 3D Human Mesh Recovery from Video with Spatio-Temporal Alignment Fusion
Getting Started
Installation & Clone the repo [Environment on Linux (Ubuntu 18.04 with python >= 3.7)]
# Install the requirements using `virtualenv`: cd$PWD/STAF
source scripts/install_pip.sh
Download the Required Data
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
Running the Demo
We have prepared a demo code to run STAF on arbitrary videos.
To do this you can just run:
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!
Citation
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={34},
number={11},
pages={10564-10577},
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}}
About
STAF: 3D Human Mesh Recovery from Video with Spatio-Temporal Alignment Fusion
