Re-ID

Leaderboard

Method	backbone	test size	Market1501	CUHK03 (detected)	CUHK03 (detected/new)	CUHK03 (labeled/new)	CUHK-SYSU	DukeMTMC-reID	MARS
			rank1 / mAP	rank1/rank5/rank10	rank1 / mAP	rank1 / mAP	rank1 / mAP		rank1 / mAP
AlignedReID	ResNet50-X		92.6 / 82.3	91.9 / 98.7 / 99.4		86.8 / 79.1			95.3 / 93.7
AlignedReID (RK)			94.0 / 91.2	96.1 / 99.5 / 99.6		87.5 / 85.6
Deep-Person(SQ)	ResNet-50	256×128	92.31 / 79.58	89.4 / 98.2 / 99.1					80.90 / 64.80
Deep-Person(MQ)	ResNet-50	256×128	94.48 / 85.09
PCB(SQ)	ResNet-50	384x128	92.4 / 77.3		61.3 / 54.2			81.9 / 65.3
PCB+RPP(SQ)	ResNet-50	384x128	93.8 / 81.6		63.7 / 57.5			83.3 / 69.2
PN-GAN (SQ)	ResNet-50		95.52 / 89.94	92.66 / 99.84 / 100					91.47 / 81.39
PN-GAN (MQ)	ResNet-50		95.90 / 91.37
MGN (SQ)	ResNet-50		95.7 / 86.9		66.8 / 66.0	68.0 / 67.4		88.7 / 78.4
MGN (MQ)	ResNet-50		96.9 / 90.7
MGN (SQ+RK)	ResNet-50		96.6 / 94.2
MGN (MQ+RK)	ResNet-50		97.1 / 95.9
HPM(SQ)	ResNet-50	384x128	94.2 / 82.7		63.1 / 57.5			86.6 / 74.3
HPM+HRE(SQ)	ResNet-50	384x128	93.9 / 83.1		63.2 / 59.7			86.3 / 74.5

Person Re-identification / Person Retrieval

DeepReID: Deep Filter Pairing Neural Network for Person Re-Identification

• intro: CVPR 2014
• paper: http://www.cv-foundation.org/openaccess/content_cvpr_2014/papers/Li_DeepReID_Deep_Filter_2014_CVPR_paper.pdf

An Improved Deep Learning Architecture for Person Re-Identification

• intro: CVPR 2015
• paper: http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Ahmed_An_Improved_Deep_2015_CVPR_paper.pdf
• github: https://github.com/Ning-Ding/Implementation-CVPR2015-CNN-for-ReID

Deep Ranking for Person Re-identification via Joint Representation Learning

• intro: IEEE Transactions on Image Processing (TIP), 2016
• arxiv: https://arxiv.org/abs/1505.06821

PersonNet: Person Re-identification with Deep Convolutional Neural Networks

• arxiv: http://arxiv.org/abs/1601.07255

Learning Deep Feature Representations with Domain Guided Dropout for Person Re-identification

• intro: CVPR 2016
• arxiv: https://arxiv.org/abs/1604.07528
• github: https://github.com/Cysu/dgd_person_reid

Person Re-Identification by Multi-Channel Parts-Based CNN with Improved Triplet Loss Function

• intro: CVPR 2016
• paper: http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Cheng_Person_Re-Identification_by_CVPR_2016_paper.pdf

Joint Learning of Single-image and Cross-image Representations for Person Re-identification

• intro: CVPR 2016
• paper: http://openaccess.thecvf.com/content_cvpr_2016/papers/Wang_Joint_Learning_of_CVPR_2016_paper.pdf

End-to-End Comparative Attention Networks for Person Re-identification

https://arxiv.org/abs/1606.04404

A Multi-task Deep Network for Person Re-identification

• intro: AAAI 2017
• arxiv: http://arxiv.org/abs/1607.05369

A Siamese Long Short-Term Memory Architecture for Human Re-Identification

• arxiv: http://arxiv.org/abs/1607.08381

Gated Siamese Convolutional Neural Network Architecture for Human Re-Identification

• intro: ECCV 2016
• keywords: Market1501 rank1 = 65.9%
• arxiv: https://arxiv.org/abs/1607.08378

Deep Neural Networks with Inexact Matching for Person Re-Identification

• intro: NIPS 2016
• keywords: Normalized correlation layer, CUHK03/CUHK01/QMULGRID
• paper: https://papers.nips.cc/paper/6367-deep-neural-networks-with-inexact-matching-for-person-re-identification
• github: https://github.com/InnovArul/personreid_normxcorr

Person Re-identification: Past, Present and Future

https://arxiv.org/abs/1610.02984

Deep Learning Prototype Domains for Person Re-Identification

• arxiv: https://arxiv.org/abs/1610.05047

Deep Transfer Learning for Person Re-identification

• arxiv: https://arxiv.org/abs/1611.05244

A Discriminatively Learned CNN Embedding for Person Re-identification

• intro: TOMM 2017
• arxiv: https://arxiv.org/abs/1611.05666
• github(official, MatConvnet): https://github.com/layumi/2016_person_re-ID
• github: https://github.com/D-X-Y/caffe-reid

Person Re-Identification via Recurrent Feature Aggregation

• intro: ECCV 2016
• keywords: recurrent feature aggregation network (RFA-Net)
• arxiv: https://arxiv.org/abs/1701.06351
• code: https://sites.google.com/site/yanyichao91sjtu/
• github(official): https://github.com/daodaofr/caffe-re-id

Structured Deep Hashing with Convolutional Neural Networks for Fast Person Re-identification

• arxiv: https://arxiv.org/abs/1702.04179

SVDNet for Pedestrian Retrieval

• intro: ICCV 2017 spotlight
• intro: On the Market-1501 dataset, rank-1 accuracy is improved from 55.2% to 80.5% for CaffeNet, and from 73.8% to 83.1% for ResNet-50
• arxiv: https://arxiv.org/abs/1703.05693
• github: https://github.com/syfafterzy/SVDNet-for-Pedestrian-Retrieval

In Defense of the Triplet Loss for Person Re-Identification

• arxiv: https://arxiv.org/abs/1703.07737
• github(Theano): https://github.com/VisualComputingInstitute/triplet-reid

Beyond triplet loss: a deep quadruplet network for person re-identification

• intro: CVPR 2017
• arxiv: https://arxiv.org/abs/1704.01719
• ppaper: http://cvip.computing.dundee.ac.uk/papers/Chen_CVPR_2017_paper.pdf

Quality Aware Network for Set to Set Recognition

• intro: CVPR 2017
• arxiv: https://arxiv.org/abs/1704.03373
• github: https://github.com/sciencefans/Quality-Aware-Network

Learning Deep Context-aware Features over Body and Latent Parts for Person Re-identification

• intro: CVPR 2017. CASIA
• keywords: Multi-Scale Context-Aware Network (MSCAN)
• arxiv: https://arxiv.org/abs/1710.06555
• supplemental: http://openaccess.thecvf.com/content_cvpr_2017/supplemental/Li_Learning_Deep_Context-Aware_2017_CVPR_supplemental.pdf

Point to Set Similarity Based Deep Feature Learning for Person Re-identification

• intro: CVPR 2017
• paper: http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhou_Point_to_Set_CVPR_2017_paper.pdf
• github(stay tuned): https://github.com/samaonline/Point-to-Set-Similarity-Based-Deep-Feature-Learning-for-Person-Re-identification

Scalable Person Re-identification on Supervised Smoothed Manifold

• intro: CVPR 2017 spotlight
• arxiv: https://arxiv.org/abs/1703.08359
• youtube: https://www.youtube.com/watch?v=bESdJgalQrg

Attention-based Natural Language Person Retrieval

• intro: CVPR 2017 Workshop (vision meets cognition)
• keywords: Bidirectional Long Short- Term Memory (BLSTM)
• arxiv: https://arxiv.org/abs/1705.08923

Part-based Deep Hashing for Large-scale Person Re-identification

• intro: IEEE Transactions on Image Processing, 2017
• arxiv: https://arxiv.org/abs/1705.02145

Deep Person Re-Identification with Improved Embedding

Deep Person Re-Identification with Improved Embedding and Efficient Training

• intro: IJCB 2017
• arxiv: https://arxiv.org/abs/1705.03332

Towards a Principled Integration of Multi-Camera Re-Identification and Tracking through Optimal Bayes Filters

• arxiv: https://arxiv.org/abs/1705.04608
• github: https://github.com/VisualComputingInstitute/towards-reid-tracking

Person Re-Identification by Deep Joint Learning of Multi-Loss Classification

• intro: IJCAI 2017
• arxiv: https://arxiv.org/abs/1705.04724

Deep Representation Learning with Part Loss for Person Re-Identification

• keywords: Part Loss Networks
• arxiv: https://arxiv.org/abs/1707.00798

Pedestrian Alignment Network for Large-scale Person Re-identification

• arxiv: https://arxiv.org/abs/1707.00408
• github: https://github.com/layumi/Pedestrian_Alignment

Learning Efficient Image Representation for Person Re-Identification

https://arxiv.org/abs/1707.02319

Person Re-identification Using Visual Attention

• intro: ICIP 2017
• arxiv: https://arxiv.org/abs/1707.07336

What-and-Where to Match: Deep Spatially Multiplicative Integration Networks for Person Re-identification

https://arxiv.org/abs/1707.07074

Deep Feature Learning via Structured Graph Laplacian Embedding for Person Re-Identification

https://arxiv.org/abs/1707.07791

Large Margin Learning in Set to Set Similarity Comparison for Person Re-identification

• intro: IEEE Transactions on Multimedia
• arxiv: https://arxiv.org/abs/1708.05512

Multi-scale Deep Learning Architectures for Person Re-identification

• intro: ICCV 2017
• arxiv: https://arxiv.org/abs/1709.05165

Person Re-Identification by Deep Learning Multi-Scale Representations

• intro: ICCV 2017
• keywords: Deep Pyramid Feature Learning (DPFL)
• paper: http://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w37/Chen_Person_Re-Identification_by_ICCV_2017_paper.pdf
• paper: http://www.eecs.qmul.ac.uk/~sgg/papers/ChenEtAl_ICCV2017WK_CHI.pdf

HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis

• intro: ICCV 2017. CUHK & SenseTime,
• arxiv: https://arxiv.org/abs/1709.09930
• github: https://github.com/xh-liu/HydraPlus-Net

Person Re-Identification with Vision and Language

https://arxiv.org/abs/1710.01202

Margin Sample Mining Loss: A Deep Learning Based Method for Person Re-identification

https://arxiv.org/abs/1710.00478

Pseudo-positive regularization for deep person re-identification

https://arxiv.org/abs/1711.06500

Let Features Decide for Themselves: Feature Mask Network for Person Re-identification

• keywords: Feature Mask Network (FMN)
• arxiv: https://arxiv.org/abs/1711.07155

AlignedReID: Surpassing Human-Level Performance in Person Re-Identification

• intro: Megvii Inc & Zhejiang University
• arxiv: https://arxiv.org/abs/1711.08184
• evaluation website: (Market1501): http://reid-challenge.megvii.com/
• evaluation website: (CUHK03): http://reid-challenge.megvii.com/cuhk03
• github: https://github.com/huanghoujing/AlignedReID-Re-Production-Pytorch

Region-based Quality Estimation Network for Large-scale Person Re-identification

• intro: AAAI 2018
• arxiv: https://arxiv.org/abs/1711.08766

Beyond Part Models: Person Retrieval with Refined Part Pooling

• keywords: Part-based Convolutional Baseline (PCB), Refined Part Pooling (RPP)
• arxiv: https://arxiv.org/abs/1711.09349

Deep-Person: Learning Discriminative Deep Features for Person Re-Identification

https://arxiv.org/abs/1711.10658

Hierarchical Cross Network for Person Re-identification

https://arxiv.org/abs/1712.06820

Re-ID done right: towards good practices for person re-identification

https://arxiv.org/abs/1801.05339

Triplet-based Deep Similarity Learning for Person Re-Identification

• intro: ICCV Workshops 2017
• arxiv: https://arxiv.org/abs/1802.03254

Group Consistent Similarity Learning via Deep CRFs for Person Re-Identification

• intro: CVPR 2018 oral

Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification

• intro: CVPR 2018
• keywords: similarity preserving generative adversarial network (SPGAN), Siamese network, CycleGAN, domain adaptation
• arxiv: https://arxiv.org/abs/1711.07027

Harmonious Attention Network for Person Re-Identification

• intro: CVPR 2018
• keywords: Harmonious Attention CNN (HA-CNN)
• arxiv: https://arxiv.org/abs/1802.08122

Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-Free Approach

• intro: CVPR 2018.
• keywords: Market1501 rank1=83.58%
• arxiv: https://arxiv.org/abs/1801.00881

Camera Style Adaptation for Person Re-identfication

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1711.10295
• github: https://github.com/zhunzhong07/CamStyle

Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1711.07027

Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1803.09937

Multi-Level Factorisation Net for Person Re-Identification

• intro: CVPR 2018
• keywords: Multi-Level Factorisation Net (MLFN)
• arxiv: https://arxiv.org/abs/1803.09132

Features for Multi-Target Multi-Camera Tracking and Re-Identification

Good Appearance Features for Multi-Target Multi-Camera Tracking

• intro: CVPR 2018 spotlight. Duke University
• keywords: adaptive weighted triplet loss, hard-identity mining
• project page: http://vision.cs.duke.edu/DukeMTMC/
• arxiv: https://arxiv.org/abs/1803.10859

Mask-guided Contrastive Attention Model for Person Re-Identification

• intro: CVPR 2018

Efficient and Deep Person Re-Identification using Multi-Level Similarity

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1803.11353

Person Re-identification with Cascaded Pairwise Convolutions

• intro: CVPR 2018

Attention-Aware Compositional Network for Person Re-identification

• intro: CVPR 2018
• intro: Sensets Technology Limited & University of Sydney
• arxiv: https://arxiv.org/abs/1805.03344

Deep Group-shuffling Random Walk for Person Re-identification

• intro: CVPR 2018

Adversarially Occluded Samples for Person Re-identification

• intro: CVPR 2018

Easy Identification from Better Constraints: Multi-Shot Person Re-Identification from Reference Constraints

• intro: CVPR 2018

Eliminating Background-bias for Robust Person Re-identification

End-to-End Deep Kronecker-Product Matching for Person Re-identification

Exploiting Transitivity for Learning Person Re-identification Models on a Budget

Resource Aware Person Re-identification across Multiple Resolutions

Multi-Channel Pyramid Person Matching Network for Person Re-Identification

• intro: 32nd AAAI Conference on Artificial Intelligence
• keywords: Multi-Channel deep convolutional Pyramid Person Matching Network (MC-PPMN)
• arxiv: https://arxiv.org/abs/1803.02558

Pyramid Person Matching Network for Person Re-identification

• intro: 9th Asian Conference on Machine Learning (ACML2017) JMLR Workshop and Conference Proceedings
• arxiv: https://arxiv.org/abs/1803.02547

Virtual CNN Branching: Efficient Feature Ensemble for Person Re-Identification

https://arxiv.org/abs/1803.05872

Adversarial Binary Coding for Efficient Person Re-identification

https://arxiv.org/abs/1803.10914

Learning View-Specific Deep Networks for Person Re-Identification

• intro: IEEE Transactions on image processing. Sun Yat-Sen University
• keywords: cross-view Euclidean constraint (CV-EC), cross-view center loss (CV-CL)
• arxiv: https://arxiv.org/abs/1803.11333

Learning Discriminative Features with Multiple Granularities for Person Re-Identification

• intro: Shanghai Jiao Tong University & CloudWalk
• keywords: Multiple Granularity Network (MGN)
• arxiv: https://arxiv.org/abs/1804.01438

Occluded Person Re-identification

• intro: ICME 2018
• arxiv: https://arxiv.org/abs/1804.02792

Recurrent Neural Networks for Person Re-identification Revisited

• intro: Stanford University & Google AI
• arxiv: https://arxiv.org/abs/1804.03281

MaskReID: A Mask Based Deep Ranking Neural Network for Person Re-identification

https://arxiv.org/abs/1804.03864

Horizontal Pyramid Matching for Person Re-identification

• intro: UIUC & IBM Research & Cornell University & Stevens Institute of Technology &CloudWalk Technology
• keywords: Horizontal Pyramid Matching (HPM), Horizontal Pyramid Pooling (HPP), horizontal random erasing (HRE)
• arxiv: https://arxiv.org/abs/1804.05275

Part-Aligned Bilinear Representations for Person Re-identification

• intro: Seoul National University & Microsoft Research & Max Planck Institute & University of Tubingen & JD.COM
• arxiv: https://arxiv.org/abs/1804.07094

Deep Co-attention based Comparators For Relative Representation Learning in Person Re-identification

https://arxiv.org/abs/1804.11027

Person Search

End-to-End Deep Learning for Person Search

Joint Detection and Identification Feature Learning for Person Search

• intro: CVPR 2017
• keywords: Online Instance Matching (OIM) loss function
• homepage(dataset+code):http://www.ee.cuhk.edu.hk/~xgwang/PS/dataset.html
• arxiv: https://arxiv.org/abs/1604.01850
• paper: http://www.ee.cuhk.edu.hk/~xgwang/PS/paper.pdf
• github(official. Caffe): https://github.com/ShuangLI59/person_search

Person Re-identification in the Wild

• intro: CVPR 2017 spotlight
• keywords: PRW dataset
• project page: http://www.liangzheng.com.cn/Project/project_prw.html
• arxiv: https://arxiv.org/abs/1604.02531
• github: https://github.com/liangzheng06/PRW-baseline
• youtube: https://www.youtube.com/watch?v=dbOGwBITJqo

IAN: The Individual Aggregation Network for Person Search

https://arxiv.org/abs/1705.05552

Neural Person Search Machines

• intro: ICCV 2017
• arxiv: https://arxiv.org/abs/1707.06777

End-to-End Detection and Re-identification Integrated Net for Person Search

• keywords: I-Net
• arxiv: https://arxiv.org/abs/1804.00376

Pose/View for Re-ID

Pose Invariant Embedding for Deep Person Re-identification

• keywords: pose invariant embedding (PIE), PoseBox fusion (PBF) CNN https://arxiv.org/abs/1701.07732

Deeply-Learned Part-Aligned Representations for Person Re-Identification

• intro: ICCV 2017
• arxiv: https://arxiv.org/abs/1707.07256
• github(official, Caffe): https://github.com/zlmzju/part_reid

Spindle Net: Person Re-identification with Human Body Region Guided Feature Decomposition and Fusion

• intro: CVPR 2017
• paper: http://openaccess.thecvf.com/content_cvpr_2017/papers/Zhao_Spindle_Net_Person_CVPR_2017_paper.pdf
• github: https://github.com/yokattame/SpindleNet

Pose-driven Deep Convolutional Model for Person Re-identification

https://arxiv.org/abs/1709.08325

A Pose-Sensitive Embedding for Person Re-Identification with Expanded Cross Neighborhood Re-Ranking

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1711.10378
• github(official): https://github.com/pse-ecn/pose-sensitive-embedding

Pose-Driven Deep Models for Person Re-Identification

• intro: Masters thesis
• arxiv: https://arxiv.org/abs/1803.08709

Pose Transferrable Person Re-Identification

• intro: CVPR 2018

Person re-identification with fusion of hand-crafted and deep pose-based body region features

https://arxiv.org/abs/1803.10630

GAN for Re-ID

Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in vitro

• intro: ICCV 2017
• arxiv: https://arxiv.org/abs/1701.07717
• github: https://github.com/layumi/Person-reID_GAN

Person Transfer GAN to Bridge Domain Gap for Person Re-Identification

• intro: CVPR 2018 spotlight
• arxiv: https://arxiv.org/abs/1711.08565

Pose-Normalized Image Generation for Person Re-identification

• keywords: PN-GAN
• arxiv: https://arxiv.org/abs/1712.02225
• github: https://github.com/naiq/PN_GAN

Multi-pseudo Regularized Label for Generated Samples in Person Re-Identification

https://arxiv.org/abs/1801.06742

Human Parsing for Re-ID

Human Semantic Parsing for Person Re-identification

• intro: CVPR 2018. SPReID
• arxiv: https://arxiv.org/abs/1804.00216

Reinforcement Learning for Re-ID

Deep Reinforcement Learning Attention Selection for Person Re-Identification

Identity Alignment by Noisy Pixel Removal

• intro: BMVC 2017
• arxiv: https://arxiv.org/abs/1707.02785
• paper: http://www.eecs.qmul.ac.uk/~sgg/papers/LanEtAl_2017BMVC.pdf

Attributes Prediction for Re-ID

Multi-Task Learning with Low Rank Attribute Embedding for Person Re-identification

• intro: ICCV 2015
• paper: http://legacydirs.umiacs.umd.edu/~fyang/papers/iccv15.pdf

Deep Attributes Driven Multi-Camera Person Re-identification

• intro: ECCV 2016
• arxiv: https://arxiv.org/abs/1605.03259

Improving Person Re-identification by Attribute and Identity Learning

https://arxiv.org/abs/1703.07220

Person Re-identification by Deep Learning Attribute-Complementary Information

• intro: CVPR 2017 workshop
• paper: https://sci-hub.tw/10.1109/CVPRW.2017.186

Video Person Re-Identification

Recurrent Convolutional Network for Video-based Person Re-Identification

• intro: CVPR 2016
• paper: http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/McLaughlin_Recurrent_Convolutional_Network_CVPR_2016_paper.pdf
• github: https://github.com/niallmcl/Recurrent-Convolutional-Video-ReID

Deep Recurrent Convolutional Networks for Video-based Person Re-identification: An End-to-End Approach

https://arxiv.org/abs/1606.01609

Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identification

• intro: ICCV 2017
• arxiv: https://arxiv.org/abs/1708.02286

Three-Stream Convolutional Networks for Video-based Person Re-Identification

https://arxiv.org/abs/1712.01652

LVreID: Person Re-Identification with Long Sequence Videos

https://arxiv.org/abs/1712.07286

Multi-shot Pedestrian Re-identification via Sequential Decision Making

• intro: CVPR 2018. TuSimple
• keywords: reinforcement learning
• arxiv: https://arxiv.org/abs/1712.07257
• github: https://github.com/TuSimple/rl-multishot-reid

Diversity Regularized Spatiotemporal Attention for Video-based Person Re-identification

• intro: CUHK-SenseTime & Argo AI
• arxiv: https://arxiv.org/abs/1803.09882

Video Person Re-identification with Competitive Snippet-similarity Aggregation and Co-attentive Snippet Embedding

• intro: CVPR 2018 Poster

Exploit the Unknown Gradually:~ One-Shot Video-Based Person Re-Identification by Stepwise Learning

• intro: CVPR 2018

Revisiting Temporal Modeling for Video-based Person ReID

• arxiv: https://arxiv.org/abs/1805.02104
• github: https://github.com/jiyanggao/Video-Person-ReID

Re-ranking

Divide and Fuse: A Re-ranking Approach for Person Re-identification

• intro: BMVC 2017
• arxiv: https://arxiv.org/abs/1708.04169

Re-ranking Person Re-identification with k-reciprocal Encoding

• intro: CVPR 2017
• arxiv: https://arxiv.org/abs/1701.08398
• github: https://github.com/zhunzhong07/person-re-ranking

A Pose-Sensitive Embedding for Person Re-Identification with Expanded Cross Neighborhood Re-Ranking

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1711.10378
• github(official): https://github.com/pse-ecn/expanded-cross-neighborhood

Unsupervised Re-ID

Unsupervised Person Re-identification: Clustering and Fine-tuning

• arxiv: https://arxiv.org/abs/1705.10444
• github: https://github.com/hehefan/Unsupervised-Person-Re-identification-Clustering-and-Fine-tuning

Stepwise Metric Promotion for Unsupervised Video Person Re-identification

• intro: ICCV 2017
• paper: http://openaccess.thecvf.com/content_ICCV_2017/papers/Liu_Stepwise_Metric_Promotion_ICCV_2017_paper.pdf
• github: https://github.com/lilithliu/StepwiseMetricPromotion-code

Dynamic Label Graph Matching for Unsupervised Video Re-Identification

• intro: ICCV 2017
• arxiv: https://arxiv.org/abs/1709.09297
• github: https://github.com/mangye16/dgm_re-id

Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatio-temporal Patterns

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1803.07293
• github: https://github.com/ahangchen/TFusion
• blog: https://zhuanlan.zhihu.com/p/34778414

Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1803.09786

Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification

• intro: CVPR 2018 workshop. National Taiwan University & Umbo Computer Vision
• keywords: adaptation and re-identification network (ARN)
• arxiv: https://arxiv.org/abs/1804.09347

Domain Adaptation through Synthesis for Unsupervised Person Re-identification

https://arxiv.org/abs/1804.10094

Vehicle Re-ID

Learning Deep Neural Networks for Vehicle Re-ID with Visual-spatio-temporal Path Proposals

• intro: ICCV 2017
• arxiv: https://arxiv.org/abs/1708.03918

Deep Metric Learning

Deep Metric Learning for Person Re-Identification

• intro: ICPR 2014
• paper: http://www.cbsr.ia.ac.cn/users/zlei/papers/ICPR2014/Yi-ICPR-14.pdf

Deep Metric Learning for Practical Person Re-Identification

https://arxiv.org/abs/1407.4979

Constrained Deep Metric Learning for Person Re-identification

https://arxiv.org/abs/1511.07545

Embedding Deep Metric for Person Re-identication A Study Against Large Variations

• intro: ECCV 2016
• arxiv: https://arxiv.org/abs/1611.00137

DarkRank: Accelerating Deep Metric Learning via Cross Sample Similarities Transfer

• intro: TuSimple
• keywords: pedestrian re-identification
• arxiv: https://arxiv.org/abs/1707.01220

Projects

Open-ReID: Open source person re-identification library in python

• intro: Open-ReID is a lightweight library of person re-identification for research purpose. It aims to provide a uniform interface for different datasets, a full set of models and evaluation metrics, as well as examples to reproduce (near) state-of-the-art results.
• project page: https://cysu.github.io/open-reid/
• github(PyTorch): https://github.com/Cysu/open-reid
• examples: https://cysu.github.io/open-reid/examples/training_id.html
• benchmarks: https://cysu.github.io/open-reid/examples/benchmarks.html

caffe-PersonReID

• intro: Person Re-Identification: Multi-Task Deep CNN with Triplet Loss
• gtihub: https://github.com/agjayant/caffe-Person-ReID

Person_reID_baseline_pytorch

• intro: Pytorch implement of Person re-identification baseline
• arxiv: https://github.com/layumi/Person_reID_baseline_pytorch

deep-person-reid

• intro: Pytorch implementation of deep person re-identification models.
• github: https://github.com/KaiyangZhou/deep-person-reid

Evaluation

DukeMTMC-reID

• intro: The Person re-ID Evaluation Code for DukeMTMC-reID Dataset (Including Dataset Download)
• github: https://github.com/layumi/DukeMTMC-reID_evaluation

DukeMTMC-reID_baseline (Matlab)

https://github.com/layumi/DukeMTMC-reID_baseline

Code for IDE baseline on Market-1501

https://github.com/zhunzhong07/IDE-baseline-Market-1501

Talks

1st Workshop on Target Re-Identification and Multi-Target Multi-Camera Tracking

https://reid-mct.github.io/

Target Re-Identification and Multi-Target Multi-Camera Tracking

http://openaccess.thecvf.com/CVPR2017_workshops/CVPR2017_W17.py

Resources

Re-id Resources

https://wangzwhu.github.io/home/re_id_resources.html