Awesome

IIDS

Pytorch implementation of Paper "Intra-Inter Camera Similarity for Unsupervised Person Re-Identification" (TPAMI 2022)

This is the extended version of IICS on CVPR2021

fig1

Installation

1. Clone code

    git clone git@github.com:SY-Xuan/IIDS.git
    cd ./IIDS

2. Install dependency python packages

    conda create --name IIDS --file requirements.txt

3. Prepare dataset

Download Market1501, DukeMTMC-ReID, MSMT17 from website and put the zip file under the directory like

./data
├── dukemtmc
│   └── raw
|       └──DukeMTMC-reID.zip
├── market1501
|   └── raw
│       └── Market-1501-v15.09.15.zip
|── msmt17
|   └── raw
|       └── MSMT17_V2.zip

Usage

1. Download trained model

2. Evaluate Model

Change the checkpoint path in the ./script/test_market.sh

sh ./script/test_market.sh

3. Train Model

You need to download ResNet-50 imagenet pretrained model and change the checkpoint path in the ./script/train_market.sh

sh ./script/train_market.sh

Results

Datasets	mAP	Rank@1	Method
Market1501	72.9%	89.5%	CVPR2021
Market1501	78.0%	91.2%	This Version
DukeMTMC-ReID	64.4%	80.0%	CVPR2021
DukeMTMC-ReID	68.7%	82.1%	This Version
MSMT17	26.9%	56.4%	CVPR2021
MSMT17	35.1%	64.4%	This Version

Citations

If you find this code useful for your research, please cite our paper:

@ARTICLE{9745321,
  author={Xuan, Shiyu and Zhang, Shiliang},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={Intra-Inter Domain Similarity for Unsupervised Person Re-Identification}, 
  year={2022},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/TPAMI.2022.3163451}}

@inproceedings{xuan2021intra,
  title={Intra-inter camera similarity for unsupervised person re-identification},
  author={Xuan, Shiyu and Zhang, Shiliang},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={11926--11935},
  year={2021}
}

Contact me

If you have any questions about this code or paper, feel free to contact me at shiyu_xuan@stu.pku.edu.cn.

Acknowledgement

Codes are built upon open-reid.