The repository for the paper "Learning Rich Features for Gait Recognition by Integrating Skeletons and Silhouettes" accepted by Multimedia Tools and Applications (DOI: https://doi.org/10.1007/s11042-023-15483-x).
As part of the Springer Nature Content Sharing Initiative, we can publicly share full-text access to a view-only version of our paper by using the following SharedIt link: https://rdcu.be/dd06A
Please refer to readme.txt for training and test.
@article{peng2023bifusion,
author="Yunjie Peng and Ma Kang and Yang Zhang and Zhiqiang He",
title="Learning Rich Features for Gait Recognition by Integrating Skeletons and Silhouettes",
journal={Multimedia Tools and Applications},
year={2023},
doi={10.1007/s11042-023-15483-x}
}