Semantic-aware Consistency Network for Cloth-changing Person Re-Identification (ACM MM, 2023) [Paper]
- Python 3.6
- Pytorch 1.6.0
- yacs
- apex
- GeForce RTX 4090 × 2
-
Clone this repo:
git clone https://github.com/Gpn-star/SCNet.git cd SCNet
-
Download datasets:
LTCC: [Offical Link]
PRCC: [Offical Link]
Vc-Clothes: [Offical Link]
DeepChange: [Offical Link] -
Download human parsing results:
LTCC: [Google Drive]
PRCC: [Google Drive]
Vc-Clothes: [Google Drive]
DeepChange: [Google Drive] -
Arrange datasets according to the following structure:
Dataset/
├── LTCC_ReID/
│ ├── ...
│ └── processed
├── PRCC/
| ├── rgb / processed
│ └── sketch
├── Vc-Clothes/
| ├── ...
| └── processed
└── DeepChange/
├── ...
└── processed
-
Replace
_C.DATA.ROOT
and_C.OUTPUT
inconfigs/default_img.py
with your owndata root path
andoutput path
, respectively. -
Run
script.sh
If you find this code useful for your research, please cite our paper:
@inproceedings{guo2023semantic,
title={Semantic-aware Consistency Network for Cloth-changing Person Re-Identification},
author={Guo, Peini and Liu, Hong and Wu, Jianbing and Wang, Guoquan and Wang, Tao},
booktitle={Proceedings of the 31st ACM International Conference on Multimedia},
pages={8730--8739},
year={2023}
}