This is the official repository of the paper "PGS: Pose-Guided Supervision for Mitigating Clothes-Changing in Person Re-Identification"
Authors: Quoc-Huy Trinh, Nhat-Tan Bui, Dinh-Hieu Hoang, Phuoc-Thao Vo Thi, Hai-Dang Nguyen, Debesh Jha, Ulas Bagci, Ngan Le, Minh-Triet Tran
Below is the visualization of our method
This implementation is on the python 3.9.0
To install all necessary packages, install via requirements.txt file with this command:
pip install -r requirements.txt
After running this script, all packages will be installed.
All of the dataset will be in the ./train_data/ folder. Copy all data to ./train_data/ folder. To get access to data, please request Market-1501, Cuhk03, DukeMTMC, LTCC, and VC-Clothes
After copy full data, change the root data path in the ./configs/swin_tiny.yaml
Base weight for the tuning can be download from SOLIDER. These weights are carefully tuning in the LU-Person, MSMT17, Market-1501, and LTCC dataset (in case clothes changing needed).
You can directly run the training script via bash run.sh or from file train.py
The following command can be used:
python train.py --config_file <path to config file>
After that, you can view the result of training via ./logs/<data name>/<project name>/
The testing can be done via bash runtest.sh or you can run file test.py
You can download our weights or base weight for pose and training from Google Drive
The following command can be used to test:
python test.py --config_file <path to config file>
After the testing the test result will be logged in the same folder as the config.
The result in test dataset can be found in our paper, below is the visualization of attention map from our paper
@article{pgs,
title={PGS: Pose-Guided Supervision for Mitigating Clothes-Changing in Person Re-Identification},
author={Quoc-Huy Trinh and Nhat-Tan Bui and Dinh-Hieu Hoang and Phuoc-Thao Vo Thi and Hai-Dang Nguyen and Debesh Jha and Ulas Bagci and Ngan Le and Minh-Triet Tran},
journal={arXiv:2312.05634},
year={2023}
}