LeaderBoard

If you notice any result or the public code that has not been included in this table, please connect Zhedong Zheng without hesitation to add the method. You are welcomed! or create pull request.

Priorities are given to papers whose codes are published.

• Supervised Learning
• Transfer Learning

Code

The 1st Place Submission to AICity Challenge 2020 re-id track [code] [paper]

Drone-based building re-id [code] [paper]

Supervised Learning

Train and Test on DukeMTMC-reID

Transfer Learning

• Train on Market-1501, Test on DukeMTMC-reID

The primary motivation is that collecting ID annotation is relatively-expensive in human resource and time cost.

Is it possible to use less annotation on the unseen dataset, especially ID labels?

Methods	Use DukeMTMC Training Data (without ID label but may use the camera ID)	Rank@1	mAP	Reference
UMDL		18.5%	7.3%	“Unsupervised cross-dataset transfer learning for person re-identification”, Peng Peixi, Tao Xiang, Yaowei Wang, Massimiliano Pontil, Shaogang Gong, Tiejun Huang, and Yonghong Tian, CVPR 2016
Verif + Identif		25.7%	12.8%	“A Discriminatively Learned Cnn Embedding for Person Re-identification”, Zhedong Zheng, Liang Zheng, and Yi Yang, TOMM 2017. [pytorch code]
PUL		30.4%	16.8%	“Unsupervised Person Re-identification: Clustering and Fine-tuning”, Hehe Fan, Liang Zheng, Yi Yang, TOMM2018 [code]
PN-GAN		29.9%	15.8%	“Pose-Normalized Image Generation for Person Re-identification” Xuelin Qian, Yanwei Fu, Tao Xiang, Wenxuan Wang, Jie Qiu, Yang Wu, Yu-Gang Jiang, Xiangyang Xue, ECCV 2018
OG-Net		31.3%	16.3%	“Parameter-Efficient Person Re-identification in the 3D Space”, Zhedong Zheng and Yi Yang, TNNLS 2022. [pytorch code]
SPGAN		41.4%	22.3%	“Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification”, Weijian Deng, Liang Zheng, Guoliang Kang, Yi Yang, Qixiang Ye, Jianbin Jiao, CVPR 2018
TJ-AIDL		44.3%	23.0%	“Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification”, Jingya Wang, Xiatian Zhu, Shaogang Gong, Wei Li, ECCV 2018
MMFA		45.3%	24.7%	“Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification”, Shan Lin, Haoliang Li, Chang-Tsun Li, Alex Chichung Kot, BMVC 2018
DG-Net		43.5%	25.4%	“Joint Discriminative and Generative Learning for Person Re-identification”, Zhedong Zheng, Xiaodong Yang, Zhiding Yu, Liang Zheng, Yi Yang and Jan Kautz, CVPR 2019. (Results are in Appendix)
SPGAN+LMP		46.4%	26.2%
HHL		46.9%	27.2%	“Generalizing A Person Retrieval Model Hetero- and Homogeneously”, Zhun Zhong, Liang Zheng, Shaozi Li, Yi Yang, ECCV 2018
BUC		47.4%	27.5%	“A Bottom-up Clustering Approach to Unsupervised Person Re-identification”, Yutian Lin, Xuanyi Dong, Liang Zheng,Yan Yan, Yi Yang, AAAI 2018
CFSM		49.8%	27.3%	“Disjoint Label Space Transfer Learning with Common Factorised Space”, Xiaobin Chang, Yongxin Yang, Tao Xiang, Timothy M. Hospedales, AAAI 2019
ARN		60.2%	33.4%	“Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification”, Yu-Jhe Li, Fu-En Yang, Yen-Cheng Liu, Yu-Ying Yeh, Xiaofei Du, and Yu-Chiang Frank Wang, CVPR 2018 Workshop
TAUDL		61.7%	43.5%	“Unsupervised Person Re-identification by Deep Learning Tracklet Association”, Minxian Li, Xiatian Zhu, and Shaogang Gong, ECCV 2018
UDARTP		68.4%	49.0%	“Unsupervised Domain Adaptive Re-Identification: Theory and Practice”, Liangchen Song, Cheng Wang, Lefei Zhang, Bo Du, Qian Zhang, Chang Huang, and Xinggang Wang, arXiv:1807.11334
PCB-PAST		72.4%	54.3%	“Self-training with progressive augmentation for unsupervised cross-domain person re-identification” Xinyu Zhang, Jiewei Cao, Chunhua Shen, and Mingyu You. ICCV 2019
SSG		73.0%	53.4%	“Self-similarity grouping: A simple unsupervised cross domain adaptation approach for person re-identification” Yang Fu, Yunchao Wei, Guanshuo Wang, Yuqian Zhou, Honghui Shi, and Thomas S Huang. ICCV 2019
MMCL		72.4%	54.5%	“Unsupervised Person Re-identification via Multi-label Classification” Dongkai Wang and Shiliang Zhang. CVPR 2020.
AD-Cluster		72.6%	54.1%	“AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification” Yunpeng Zhai, Shijian Lu, Qixiang Ye, Xuebo Shan, Jie Chen, Rongrong Ji, and Yonghong Tian. CVPR 2020
B-SNR+GDS-H		76.7%	59.7%	“Global Distance-distributions Separation for Unsupervised Person Re-identification” Xin Jin, Cuiling Lan, Wenjun Zeng, Zhibo Chen. ECCV 2020
NRMT		77.8%	62.2%	“Unsupervised domain adaptation with noise resistible mutual-training for person re-identification” Fang Zhao, Shengcai Liao, Guo-Sen Xie, Jian Zhao, Kaihao Zhang, and Ling Shao. ECCV 2020
DAAM		77.6%	63.9%	“Domain Adaptive Attention Model for Unsupervised Cross-Domain Person Re-Identification” Yangru Huang, Peixi Peng, Yi Jin, Junliang Xing, Congyan Lang, Songhe Feng. AAAI 2020
MMT		78.0%	65.1%	“Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification” Yixiao Ge, Dapeng Chen, Hongsheng Li. ICLR 2020
DGNet++		78.9%	63.8%	“Joint disentangling and adaptation for cross-domain person re-identification” Yang Zou, Xiaodong Yang, Zhiding Yu, B.V.K. Vijaya Kumar, Jan Kautz. ECCV20
MEB-Net		79.6%	66.1%	“Multiple expert brainstorming for domain adaptive person re-identification” Yunpeng Zhai, Qixiang Ye, Shijian Lu, Mengxi Jia, Rongrong Ji, Yonghong Tian. ECCV 2020
UNRN		82.0%	69.1%	“Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification” Kecheng Zheng, Cuiling Lan, Wenjun Zeng, Zhizheng Zhang, and Zheng-Jun Zha. AAAI 2021
Cluster Contrast + GEM		86.8%	76.0%	“Cluster Contrast for Unsupervised Person Re-Identification” Dai, Zuozhuo and Wang, Guangyuan and Zhu, Siyu and Yuan, Weihao and Tan, Ping. arXiv 2021

Train on MSMT17, Test on DukeMTMC-reID

Methods	Use DukeMTMC Training Data (without ID label but may use the camera ID)	Rank@1	mAP	Reference
Verif + Identif		48.7%	27.5%	“A Discriminatively Learned Cnn Embedding for Person Re-identification”, Zhedong Zheng, Liang Zheng, and Yi Yang, TOMM 2017. [pytorch code]
OG-Net		31.3%	16.3%	“Parameter-Efficient Person Re-identification in the 3D Space”, Zhedong Zheng and Yi Yang, TNNLS 2022. [pytorch code]
DG-Net		62.0%	40.7%	“Joint Discriminative and Generative Learning for Person Re-identification”, Zhedong Zheng, Xiaodong Yang, Zhiding Yu, Liang Zheng, Yi Yang and Jan Kautz, CVPR 2019. [code] (Results are in Appendix)
MAR		67.1%	48.0%	“Unsupervised Person Re-identification by Soft Multilabel Learning”, Hong-Xing Yu, Wei-Shi Zheng, Ancong Wu, Xiaowei Guo, Shaogang Gong, Jian-Huang Lai, CVPR 2019.
UDARTP		75.0%	57.1%	“Unsupervised Domain Adaptive Re-Identification: Theory and Practice”, Liangchen Song, Cheng Wang, Lefei Zhang, Bo Du, Qian Zhang, Chang Huang, and Xinggang Wang, arXiv:1807.11334

Train on MSMT17, Test on Market

Methods	Use Market Training Data (without ID label but may use the camera ID)	Rank@1	mAP	Reference
OG-Net		40.1%	17.6%	“Parameter-Efficient Person Re-identification in the 3D Space”, Zhedong Zheng and Yi Yang, TNNLS 2022. [pytorch code]
DG-Net		61.8%	33.6%	“Joint Discriminative and Generative Learning for Person Re-identification”, Zhedong Zheng, Xiaodong Yang, Zhiding Yu, Liang Zheng, Yi Yang and Jan Kautz, CVPR 2019. [code] (Results are in Appendix)

DukeMTMC-reID Protocol Citation

@inproceedings{zheng2017unlabeled,
  title={Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro},
  author={Zheng, Zhedong and Zheng, Liang and Yang, Yi},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
  year={2017}
}

@inproceedings{ristani2016MTMC,
  title = {Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking},
  author = {Ristani, Ergys and Solera, Francesco and Zou, Roger and Cucchiara, Rita and Tomasi, Carlo},
  booktitle = {European Conference on Computer Vision workshop on Benchmarking Multi-Target Tracking},
  year = {2016}
}