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@ -48,14 +48,15 @@ The new training/testing protocol split for CUHK03 in our paper is in the "evalu
### State-of-the-art ### State-of-the-art
|--- | Labeled | Labeled| detected | detected| | | - | Labeled | Labeled| detected | detected| |
| -------| ----- | ---- |---- |---- |---- | | -------| ----- | ---- |---- |---- |---- |
|Methods | Rank@1 | mAP| Rank@1 | mAP| Reference | |Methods | Rank@1 | mAP| Rank@1 | mAP| Reference |
|BOW+XQDA| 7.93% | 7.29%|6.36% | 6.39%|"[Scalable person re-identification: a benchmark](http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7410490)", Zheng Liang, Shen Liyue, Tian Lu, Wang Shengjin, Wang Jingdong and Tian, Qi, ICCV 2015 [[project]](http://www.liangzheng.org/Project/project_reid.html)| |BOW+XQDA| 7.93% | 7.29%|6.36% | 6.39%|"[Scalable person re-identification: a benchmark](http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7410490)", Zheng Liang, Shen Liyue, Tian Lu, Wang Shengjin, Wang Jingdong and Tian, Qi, ICCV 2015 [[project]](http://www.liangzheng.org/Project/project_reid.html)|
|PUL| - | -|9.1% | 9.2%|"[Unsupervised Person Re-identification: Clustering and Fine-tuning](https://arxiv.org/pdf/1705.10444.pdf)", Hehe Fan, Liang Zheng and Yi Yang, arXiv:1705.10444 [[code]](https://github.com/hehefan/Unsupervised-Person-Re-identification-Clustering-and-Fine-tuning)|
|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)| |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| 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+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.+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)|
|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 [[code]](https://github.com/layumi/Pedestrian_Alignment)| |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)|
|PAN+re-ranking| 43.9% | 45.8%|41.9% | 43.8%| "[Pedestrian Alignment Network for Person Re-identification](https://arxiv.org/abs/1707.00408)", Zhedong Zheng, Liang Zheng, Yi Yang, arxiv [[code]](https://github.com/layumi/Pedestrian_Alignment)| |PAN+re-ranking| 43.9% | 45.8%|41.9% | 43.8%| "[Pedestrian Alignment Network for Person Re-identification](https://arxiv.org/abs/1707.00408)", Zhedong Zheng, Liang Zheng, Yi Yang, arxiv [[code]](https://github.com/layumi/Pedestrian_Alignment)|