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Generalizing A Person Retrieval Model Hetero- and Homogeneously
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Code for Generalizing A Person Retrieval Model Hetero- and Homogeneously (ECCV 2018). [paper]
Preparation
Requirements: Python=3.6 and Pytorch=0.4.0
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Install Pytorch
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Download dataset
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reid_dataset [GoogleDriver]
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The reid_dataset including Market-1501 (with CamStyle), DukeMTMC-reID (with CamStyle), and CUHK03
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Unzip reid_dataset under 'HHL/data/'
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CamStyle Generation
You can train CamStyle model and generate CamStyle imgaes with stargan4reid
Training and test domain adaptation model for person re-ID
- Baseline
# For Duke to Market-1501
python baseline.py -s duke -t market --logs-dir logs/duke2market-baseline
# For Market-1501 to Duke
python baseline.py -s market -t duke --logs-dir logs/market2duke-baseline
- HHL
# For Duke to Market-1501
python HHL.py -s duke -t market --logs-dir logs/duke2market-HHL
# For Market-1501 to Duke
python HHL.py -s market -t duke --logs-dir logs/market2duke-HHL
Results
<table> <tr> <td></td> <td colspan="2">Duke to Market</td> <td colspan="2">Market to Duke</td> </tr> <tr> <td>Methods</td> <td>Rank-1</td> <td>mAP</td> <td>Rank-1</td> <td>mAP</td> </tr> <tr> <td>Baseline</td> <td>44.6</td> <td>20.6</td> <td>32.9</td> <td>16.9</td> </tr> <tr> <td>HHL</td> <td>62.2</td> <td>31.4</td> <td>46.9</td> <td>27.2</td> </tr> </table>References
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[1] Our code is conducted based on open-reid
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[2] StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation , CVPR 2018
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[3] Camera Style Adaptation for Person Re-identification. CVPR 2018.
Citation
If you find this code useful in your research, please consider citing:
@inproceedings{zhong2018generalizing,
title={Generalizing A Person Retrieval Model Hetero- and Homogeneously},
author={Zhong, Zhun and Zheng, Liang and Li, Shaozi and Yang, Yi},
booktitle ={ECCV},
year={2018}
}
Contact me
If you have any questions about this code, please do not hesitate to contact me.