Implementation of Separable Spatial-Temporal Residual Graph for Cloth-Changing Group Re-Identification (TPAMI'24), including datasets (GroupPRCC and GroupVC) and method (SSRG).

Please refer to CCGReID_Dataset_README.md.

First refer to INSTALL.md. After that, the PyTorch Geometric package is also needed.

Download the CCGReID dataset and modify the dataset path. Line 23 and 73 in prcc.py .

dataset_dir = XXX

Maybe you should also keep the same dataset folder name in line 31.

Same operations in vc.py.

Download the ViT Pre-trained model and modify the path, line 11 in SSRG.yml:

PRETRAIN_PATH: XXX

Single or multiple GPU training is supported. Please refer to scripts folder.

Codebase from fast-reid. So please refer to that repository for more usage.

If you find this code useful for your research, please kindly cite the following papers:

@ARTICLE{10443971,
  author={Zhang, Quan and Lai, Jianhuang and Xie, Xiaohua and Jin, Xiaofeng and Huang, Sien},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={Separable Spatial-Temporal Residual Graph for Cloth-Changing Group Re-Identification}, 
  year={2024},
  volume={},
  number={},
  pages={1-16},
  doi={10.1109/TPAMI.2024.3369483}}

@InProceedings{Zhang_2022_CVPR,
    author    = {Zhang, Quan and Dang, Kaiheng and Lai, Jian-Huang and Feng, Zhanxiang and Xie, Xiaohua},
    title     = {Modeling 3D Layout for Group Re-Identification},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
    month     = {June},
    year      = {2022},
    pages     = {7512-7520}
}

If you have any question, please feel free to contact me. E-mail: [email protected]