/feature_learning

2019 AI City Challenge in CVPR'19, Track 2, 3rd place

Primary LanguagePythonMIT LicenseMIT

Vehicle ReID_baseline

Baseline model (with bottleneck) for vehicle ReID (using softmax and triplet loss).

Feature_Learning

This part is for learning feature extractor. The code is modified form reid_baseline, you can check each folder's purpose by yourself.

REFERENCE

Lv, K., Deng, W., Hou, Y., Du, H., Sheng, H., Jiao, J., & Zheng, L. (2019). Vehicle reidentification with the location and time stamp. In Proc. CVPR Workshops.

@inproceedings{lv2019vehicle,
 title={Vehicle reidentification with the location and time stamp},
 author={Lv, Kai and Deng, Weijian and Hou, Yunzhong and Du, Heming and Sheng, Hao and Jiao, Jianbin and Zheng, Liang},
 booktitle={Proc. CVPR Workshops},
 year={2019}
}

If you have any question, please contact us by E-mail (dengwj16@gmail.com) or open an issue in this project. Thanks.