Feature Completion for Occluded Person Re-Identification

Training and test

1. we first generate the part masks with the code https://github.com/Engineering-Course/LIP_JPPNet/.
2. python train.py --root "your path to the dataset" --fore_dir "your path to extracted foremaps"
3. python train.py --root "your path to the dataset" --fore_dir "your path to extracted foremaps" --resume "path to model.pth" --evaluate

Citation

If you use our code in your research, please use the following BibTeX entry.

@article{hou2021RFCnet,
 title={Feature Completion for Occluded Person Re-Identification},
 author={Ruibing Hou and Bingpeng Ma and Hong Chang and Xinqian Gu and Shiguang Shan and Xilin Chen},
 journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
 year={2020},
 publisher={IEEE}
}