Awesome
SAAI
The implementation of ICCV 2023 Visible-Infrared Person Re-Identification via Semantic Alignment and Affinity Inference.
:sparkles: News
- 2023-8-26: Release codes and our pretrained models at Baidudisk (7p3w).
Getting Started
Testing
- Download the dataset and pretrained models (checkpoints) from Baidudisk (7p3w), unzip them.
- Download the training data SYSU, unzip and put it in correct position.
- Download the rand_perm_cam.mat, and put it in correct position.
- Change the dataset path in the file
configs/default/dataset.py
- Run the following command to retrain the model. You need about 22G GPU for the training.
chmod 755 test.sh
./test
Training
- Download the training data SYSU, unzip and put it in correct position.
- Change the dataset path in the file
configs/default/dataset.py
- Run the following command to retrain the model. You need about 22G GPU for the training.
chmod 755 train.sh
./train
Requirement
numpy==1.24.2
torch==2.0.0
torchvision==0.15.1
PyYAML==6.0
pytorch-ignite==0.1.2
Citation
If you find our work useful for your research, please consider citing the following papers :)
@InProceedings{Fang_2023_ICCV,
author = {Fang, Xingye and Yang, Yang and Fu, Ying},
title = {Visible-Infrared Person Re-Identification via Semantic Alignment and Affinity Inference},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2023},
pages = {11270-11279}
}
Contact
If you find any problem, please feel free to contact me (fangxingye@bit.edu.cn). A brief self-introduction is required, if you would like to get an in-depth help from me.