An official implementation of our CVPR'23 paper:
《Good is Bad: Causality Inspired Cloth-Debiasing for Cloth-Changing Person Re-Identification》
[Paper Link] [Repo] [About Me]
2023.10.24 The full codes are released!
- Python 3.6
- Pytorch 1.6.0
- yacs
- apex (remind: the apex is optional, not recommended if you have enough GPU memory; just comment all amp related codes)
| RRCC | LTCC | |||||||
| Standard | Cloth-Changing | Standard | Cloth-Changing | |||||
| R@1 | mAP | R@1 | mAP | R@1 | mAP | R@1 | mAP | |
| Paper | 100.0 | 99.9 | 57.9 | 58.3 | 76.3 | 41.1 | 40.6 | 19.1 |
| Repo | 100.0 | 99.8 | 58.2 | 58.0 | 75.9 | 41.7 | 40.8 | 19.2 |
PRCC is available at Here.
LTCC is available at Here.
LaST is available at Here.
The trained models (weights) are available at Baidu Disk or Google Drive.
You will find the testing script for prcc and ltcc at test_AIM.sh, then modify the resume path to your own path where you placed the weights file.
To be noticed, you need to modify the DATA ROOT and OUTPUT in the configs/default_img.py to your own path before testing.
If you find our work useful in your research, please consider citing:
@inproceedings{yang2023good,
title={Good is bad: Causality inspired cloth-debiasing for cloth-changing person re-identification},
author={Yang, Zhengwei and Lin, Meng and Zhong, Xian and Wu, Yu and Wang, Zheng},
booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
pages={1472--1481},
year={2023}
}