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@ -57,13 +57,21 @@ If you use CUHK03-NP in your experiment, please consider citing:
|LOMO+XQDA| 14.8% | 13.6%|12.8% | 11.5%|"[Person Re-identification by Local Maximal Occurrence Representation and Metric Learning](https://arxiv.org/abs/1406.4216)", Liao Shengcai, Hu Yang, Zhu Xiangyu and Li Stan Z, CVPR 2015 [[project]](http://www.cbsr.ia.ac.cn/users/scliao/projects/lomo_xqda/index.html)|
|IDE| 22.2% | 21.0%|21.3% | 19.7%|"[Person Re-identification: Past, Present and Future](https://arxiv.org/abs/1610.02984)", Zheng Liang, Yi Yang, and Alexander G. Hauptmann, arXiv:1610.02984 [[code]](https://github.com/zhunzhong07/IDE-baseline-Market-1501)|
|IDE+DaF| 27.5%| 31.5% | 26.4% | 30.0|"[Divide and Fuse: A Re-ranking Approach for Person Re-identification](https://arxiv.org/abs/1708.04169)", Rui Yu, Zhichao Zhou, Song Bai, Xiang Bai, BMVC 2017
|IDE+XQ.+re-ranking | 38.1% | 40.3%|34.7% | 37.4%| "[Re-ranking Person Re-identification with k-reciprocal Encoding](http://zhunzhong.site/paper/re-ranking-cvpr.pdf)", Zhun Zhong, Liang Zheng, Donglin Cao,Shaozi Li, CVPR 2017 [[code]](https://github.com/zhunzhong07/person-re-ranking)|
|IDE+XQ.+RR | 38.1% | 40.3%|34.7% | 37.4%| "[Re-ranking Person Re-identification with k-reciprocal Encoding](http://zhunzhong.site/paper/re-ranking-cvpr.pdf)", Zhun Zhong, Liang Zheng, Donglin Cao,Shaozi Li, CVPR 2017 [[code]](https://github.com/zhunzhong07/person-re-ranking)|
|PAN| 36.9% | 35.0%|36.3% | 34.0%| "[Pedestrian Alignment Network for Person Re-identification](https://arxiv.org/abs/1707.00408)", Zhedong Zheng, Liang Zheng, Yi Yang, arXiv:1707.00408 [[code]](https://github.com/layumi/Pedestrian_Alignment)|
|DPFL | 43.0% | 40.5%|40.7% | 37.0%| "[Person Re-Identification by Deep Learning Multi-Scale Representations](http://www.eecs.qmul.ac.uk/~sgg/papers/ChenEtAl_ICCV2017WK_CHI.pdf?nsukey=bFKy637SdfiMPVNHqNPm9DbM4V%2BJvHS3xsL4zYv0aecUKkedzKZC304%2FT4Ot96qbKCoD%2BbcV7OA92VISMCiqLzSj4%2BBCbF3cYAmodWYkUhcK%2FFYRtZ3LLKff1Fb0GVNplfrcVq%2B%2BJJ2QO5uMDyiIFth9%2BAhb8Ib%2FZ0%2FkZyqB9rnsLKHkBXa6SI5OMMibGklQ)", Yanbei Chen, Xiatian Zhu, Shaogang Gong|
|SVDNet| 40.93 | 37.83|41.5% | 37.26%| "[SVDNet for Pedestrian Retrieval](https://arxiv.org/abs/1703.05693)", Sun Yifan, Zheng Liang, Deng Weijian, Wang Shengjin, ICCV 2017|
|HA-CNN| 44.4%| 41.0% |41.7% |38.6%| "[Harmonious Attention Network for Person Re-Identification](https://arxiv.org/pdf/1802.08122.pdf)", Wei Li1 Xiatian Zhu2 Shaogang Gong1, CVPR 2018|
|HCN+XQDA+re-rank| 43.7%| 45.3%| 44.0%| 46.9%| "[HIERARCHICAL CROSS NETWORK FOR PERSON RE-IDENTIFICATION](https://arxiv.org/pdf/1712.06820.pdf)", Huan-Cheng Hsu1, Ching-Hang Chen2, Hsiao-Rong Tyan3, Hong-Yuan Mark Liao, arxiv 2017|
|HCN+XQDA+RR| 43.7%| 45.3%| 44.0%| 46.9%| "[HIERARCHICAL CROSS NETWORK FOR PERSON RE-IDENTIFICATION](https://arxiv.org/pdf/1712.06820.pdf)", Huan-Cheng Hsu1, Ching-Hang Chen2, Hsiao-Rong Tyan3, Hong-Yuan Mark Liao, arxiv 2017|
|MLFN| 54.7% | 49.2%| 52.8%| 47.8%| "[Multi-Level Factorisation Net for Person Re-Identification](https://arxiv.org/pdf/1803.09132.pdf)", Xiaobin Chang, Timothy M. Hospedales, Tao Xiang， CVPR 2018|
|TriNet+Random Erasing| 58.14% | 53.83% | 55.50% | 50.74%| "[Random Erasing Data Augmentation](https://arxiv.org/abs/1708.04896)", Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, Yi Yang, arXiv 2017|
|TriNet+Random Erasing+Re.| 63.93% | 65.05% | 64.43% | 64.75%| "[Random Erasing Data Augmentation](https://arxiv.org/abs/1708.04896)", Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, Yi Yang, arXiv 2017|
|DaRe| 58.1% | 53.7% | 55.1% | 51.3%| "[Resource Aware Person Re-identification across Multiple Resolutions](http://www.cs.cornell.edu/~gaohuang/papers/Anytime-ReID.pdf)", Yan Wang, Lequn Wang, Yurong You, Xu Zou, Vincent Chen. CVPR 2018|
|TriNet+RE| 58.14% | 53.83% | 55.50% | 50.74%| "[Random Erasing Data Augmentation](https://arxiv.org/abs/1708.04896)", Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, Yi Yang, arXiv 2017|
|TriNet+RR+RE| 63.93% | 65.05% | 64.43% | 64.75%| "[Random Erasing Data Augmentation](https://arxiv.org/abs/1708.04896)", Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, Yi Yang, arXiv 2017|
|PCB (RPP)| - | - | 63.7% | 67.5%| "[Beyond Part Models: Person Retrieval with Refined Part Pooling (and A Strong Convolutional Baseline)](https://arxiv.org/pdf/1711.09349.pdf)", Yifan Sun, Liang Zheng, Yi Yang, Qi Tian, Shengjin Wang, arXiv 2017|
|HPM+HRE| - | - | 63.2% | 59.7%| "[Horizontal Pyramid Matching for Person Re-identification](https://arxiv.org/pdf/1804.05275.pdf)", Yang Fu1, Yunchao Wei1, Yuqian Zhou1, Honghui Shi, arXiv 2018|
|MGN| 68.0% | 67.4% | 66.8% | 66%| "[Learning Discriminative Features with Multiple Granularity for Person Re-Identification](https://arxiv.org/pdf/1804.01438.pdf)", Guanshuo Wang1, Yufeng Yuan2, Xiong Chen2, Jiwei Li2, Xi Zhou, arXiv 2018|
|DaRe(R)+RE+RR| 72.9% | 73.7% | 69.8% | 71.2%| "[Resource Aware Person Re-identification across Multiple Resolutions](http://www.cs.cornell.edu/~gaohuang/papers/Anytime-ReID.pdf)", Yan Wang, Lequn Wang, Yurong You, Xu Zou, Vincent Chen. CVPR 2018|
- RR (Re-ranking) Re-ranking person re-identification with k-reciprocal encoding. Z. Zhong, L. Zheng, D. Cao, and S. Li. CVPR 2017. [[code]](https://github.com/zhunzhong07/person-re-ranking)
- RE (Random Erasing) Random erasing data augmentation. Z. Zhong, L. Zheng, G. Kang, S. Li, and Y. Yang. arXiv, 2017. [[Code]](https://github.com/zhunzhong07/Random-Erasing)