Re-ID

Leaderboard

ReID

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
DG-Net	ResNet-50	256×128	94.8/ 86.0		65.6/61.1			86.6/74.8
AlignedReID	ResNet50-X		92.6 / 82.3	91.9 / 98.7 / 99.4		86.8 / 79.1			95.3 / 93.7
Deep-Person	ResNet-50	256×128	92.31 / 79.58	89.4 / 98.2 / 99.1					80.90 / 64.80
PCB	ResNet-50	384x128	92.4 / 77.3		61.3 / 54.2			81.9 / 65.3
PCB+RPP	ResNet-50	384x128	93.8 / 81.6		63.7 / 57.5			83.3 / 69.2
PN-GAN	ResNet-50		89.43 / 72.58	79.76 / 96.24 / 98.56				73.58 / 53.20
MGN	ResNet-50		95.7 / 86.9		66.8 / 66.0	68.0 / 67.4		88.7 / 78.4
HPM	ResNet-50	384x128	94.2 / 82.7		63.1 / 57.5			86.6 / 74.3
HPM+HRE	ResNet-50	384x128	93.9 / 83.1		63.2 / 59.7			86.3 / 74.5
SphereReID	ResNet-50	288×144	94.4 / 83.6	93.1 / 98.7 / 99.4	63.2 / 59.7		95.4 / 93.9	83.9 / 68.5
Auto-ReID		384x128	94.5 / 85.1		73.3 / 69.3	77.9 / 73.0		88.5 / 75.1

PersonSearch

Method	backbone	CUHK-SYSU	PRW	PRW-mini
		top1 / mAP	top1 / mAP	top1 / mAP
Joint Detection and Identification Feature Learning for Person Search	ResNet-50	78.7 / 75.5	– / –	– / –
Learning Context Graph for Person Search	ResNet-50	86.5 / 84.1	73.6 / 33.4	– / –
Knowledge Distillation for End-to-End Person Search	ResNet-50	88.5 / 87.2	– / –	70.0 / 33.1
Query-guided End-to-End Person Search	ResNet-50	89.1 / 88.9	76.7 / 37.1	80.0 / 39.1
Fast Person Search Pipeline	ResNet-50	89.87 / 86.99	70.58/ 44.45	– / –
End-to-End Thorough Body Perception for Person Search	ResNet-50	90.5 / 88.4	68.9 / 42.9	– / –
Re-ID Driven Localization Refinement for Person Search	ResNet-50	94.2 / 93.0	70.2 / 42.9	– / –

Papers

Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification

• intro: AAAI 2020
• arxiv: https://arxiv.org/abs/2001.05197

Robust Re-Identification by Multiple Views Knowledge Distillation

• intro: ECCV 2020
• intro: University of Modena and Reggio Emilia
• arxiv: https://arxiv.org/abs/2007.04174
• github: https://github.com/aimagelab/VKD

Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID

• intro: NeurIPS 2020
• intro: CUHK
• project apge: https://geyixiao.com/projects/spcl.html
• arxiv: https://arxiv.org/abs/2006.02713
• github: https://github.com/yxgeee/SpCL
• github: https://github.com/open-mmlab/OpenUnReID

Context-Aware Graph Convolution Network for Target Re-identification

• intro: AAAI 2021
• intro: SenseTime Research & Xidian University & Peking University
• arxiv: https://arxiv.org/abs/2012.04298

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(official, 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

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

Deep Cosine Metric Learning for Person Re-Identification

• intro: WACV 2018
• paper: https://elib.dlr.de/116408/1/WACV2018.pdf
• github: https://github.com/nwojke/cosine_metric_learning

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

• intro: ECCV 2018
• keywords: Part-based Convolutional Baseline (PCB), Refined Part Pooling (RPP)
• arxiv: https://arxiv.org/abs/1711.09349
• github: https://github.com/syfafterzy/PCB_RPP_for_reID

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
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Group_Consistent_Similarity_CVPR_2018_paper.pdf
• github(official, PyTorch): https://github.com/dapengchen123/crf_affinity

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

Similarity-preserving Image-image Domain Adaptation for Person Re-identification

https://arxiv.org/abs/1811.10551

Harmonious Attention Network for Person Re-Identification

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

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
• intro: 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
• keywords: MGCAM
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Song_Mask-Guided_Contrastive_Attention_CVPR_2018_paper.pdf
• github: https://github.com/developfeng/MGCAM

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
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Person_Re-Identification_With_CVPR_2018_paper.pdf

Attention-Aware Compositional Network for Person Re-identification

• intro: CVPR 2018
• intro: Sensets Technology Limited & University of Sydney
• keywords: Attention-Aware Compositional Network (AACN), Pose-guided Part Attention (PPA), Attention-aware Feature Composition (AFC)
• arxiv: https://arxiv.org/abs/1805.03344

Deep Group-shuffling Random Walk for Person Re-identification

• intro: CVPR 2018
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Deep_Group-Shuffling_Random_CVPR_2018_paper.pdf
• github: https://github.com/YantaoShen/kpm_rw_person_reid

Adversarially Occluded Samples for Person Re-identification

• intro: CVPR 2018
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Adversarially_Occluded_Samples_CVPR_2018_paper.pdf
• github: https://github.com/huanghoujing/AOS4ReID

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

• intro: CVPR 2018
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Easy_Identification_From_CVPR_2018_paper.pdf

Eliminating Background-bias for Robust Person Re-identification

• intro: CVPR 2018
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Tian_Eliminating_Background-Bias_for_CVPR_2018_paper.pdf

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

• intro: CVPR 2018
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_End-to-End_Deep_Kronecker-Product_CVPR_2018_paper.pdf
• github: https://github.com/YantaoShen/kpm_rw_person_reid

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

• intro: CVPR 2018
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Roy_Exploiting_Transitivity_for_CVPR_2018_paper.pdf

Resource Aware Person Re-identification across Multiple Resolutions

• intro: CVPR 2018
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Resource_Aware_Person_CVPR_2018_paper.pdf
• arxiv: https://arxiv.org/abs/1805.08805

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

Weighted Bilinear Coding over Salient Body Parts for Person Re-identification

https://arxiv.org/abs/1803.08580

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: ACM Multimedia 2018
• intro: Shanghai Jiao Tong University & CloudWalk
• keywords: Multiple Granularity Network (MGN)
• arxiv: https://arxiv.org/abs/1804.01438
• video: https://edu.csdn.net/course/play/8426

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: AAAI 2019
• 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
• github: https://github.com/OasisYang/HPM

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

https://arxiv.org/abs/1804.11027

Feature Affinity based Pseudo Labeling for Semi-supervised Person Re-identification

https://arxiv.org/abs/1805.06118

Semantically Selective Augmentation for Deep Compact Person Re-Identification

https://arxiv.org/abs/1806.04074

SphereReID: Deep Hypersphere Manifold Embedding for Person Re-Identification

• keywords: Sphere Loss, feature normalization, weight normalization, balanced sampling
• arxiv: https://arxiv.org/abs/1807.00537

Multi-task Mid-level Feature Alignment Network for Unsupervised Cross-Dataset Person Re-Identification

• intro: BMVC 2018
• intro: University of Warwick & Nanyang Technological University & Charles Sturt University
• arxiv: https://arxiv.org/abs/1807.01440

Discriminative Feature Learning with Foreground Attention for Person Re-Identification

https://arxiv.org/abs/1807.01455

Part-Aligned Bilinear Representations for Person Re-identification

• intro: ECCV 2018
• intro: Seoul National University & Microsoft Research & Max Planck Institute & University of Tubingen & JD.COM
• arxiv: https://arxiv.org/abs/1804.07094
• github: https://github.com/yuminsuh/part_bilinear_reid

Mancs: A Multi-task Attentional Network with Curriculum Sampling for Person Re-identification

• intro: ECCV 2018. Huazhong University of Science and Technology & Horizon Robotics Inc.

Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association

• intro: ECCV 2018
• arxiv: https://arxiv.org/abs/1808.01571

Deep Sequential Multi-camera Feature Fusion for Person Re-identification

https://arxiv.org/abs/1807.07295

Improving Deep Models of Person Re-identification for Cross-Dataset Usage

• intro: AIAI 2018 (14th International Conference on Artificial Intelligence Applications and Innovations) proceeding
• arxiv: https://arxiv.org/abs/1807.08526

Measuring the Temporal Behavior of Real-World Person Re-Identification

https://arxiv.org/abs/1808.05499

Alignedreid＋+: Dynamically Matching Local Information for Person Re-Identification

https://github.com/michuanhaohao/AlignedReID

Sparse Label Smoothing for Semi-supervised Person Re-Identification

• arxiv: https://arxiv.org/abs/1809.04976
• github: https://github.com/jpainam/SLS_ReID

In Defense of the Classification Loss for Person Re-Identification

• intro: University of Science and Technology of China & Microsoft Research Asia
• arxiv: https://arxiv.org/abs/1809.05864

FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification

• intro: NIPS 2018
• arxiv: https://arxiv.org/abs/1810.02936
• github(Pytorch, official): https://github.com/yxgeee/FD-GAN

Image-to-Video Person Re-Identification by Reusing Cross-modal Embeddings

https://arxiv.org/abs/1810.03989

Attention Driven Person Re-identification

• intro: Pattern Recognition (PR)
• arxiv: https://arxiv.org/abs/1810.05866

A Coarse-to-fine Pyramidal Model for Person Re-identification via Multi-Loss Dynamic Training

• intro: YouTu Lab, Tencent
• arxiv: https://arxiv.org/abs/1810.12193

M2M-GAN: Many-to-Many Generative Adversarial Transfer Learning for Person Re-Identification

https://arxiv.org/abs/1811.03768

Batch Feature Erasing for Person Re-identification and Beyond

• arxiv: https://arxiv.org/abs/1811.07130
• github(official, Pytorch): https://github.com/daizuozhuo/batch-feature-erasing-network

Re-Identification with Consistent Attentive Siamese Networks

https://arxiv.org/abs/1811.07487

One Shot Domain Adaptation for Person Re-Identification

https://arxiv.org/abs/1811.10144

Parameter-Free Spatial Attention Network for Person Re-Identification

• arxiv: https://arxiv.org/abs/1811.12150
• github: https://github.com/HRanWang/Spatial-Attention

Spectral Feature Transformation for Person Re-identification

• intro: University of Chinese Academy of Sciences & TuSimple
• arxiv: https://arxiv.org/abs/1811.11405

Identity Preserving Generative Adversarial Network for Cross-Domain Person Re-identification

https://arxiv.org/abs/1811.11510

Dissecting Person Re-identification from the Viewpoint of Viewpoint

https://arxiv.org/abs/1812.02162

Fast and Accurate Person Re-Identification with RMNet

• intro: IOTG Computer Vision (ICV), Intel
• arxiv: https://arxiv.org/abs/1812.02465

Spatial-Temporal Person Re-identification

• intro: AAAI 2019
• intro: Sun Yat-sen University
• arxiv: https://arxiv.org/abs/1812.03282
• github: https://github.com/Wanggcong/Spatial-Temporal-Re-identification

Omni-directional Feature Learning for Person Re-identification

• intro: Tongji University
• keywords: OIM loss
• arxiv: https://arxiv.org/abs/1812.05319

Learning Incremental Triplet Margin for Person Re-identification

• intro: AAAI 2019 spotlight
• intro: Hikvision Research Institute
• arxiv: https://arxiv.org/abs/1812.06576

Densely Semantically Aligned Person Re-Identification

• intro: USTC & MSRA
• arxiv: https://arxiv.org/abs/1812.08967

EANet: Enhancing Alignment for Cross-Domain Person Re-identification

• intro: CRISE & CASIA & Horizon Robotics
• arxiv: https://arxiv.org/abs/1812.11369
• github(official, Pytorch): https://github.com/huanghoujing/EANet
• blog: https://zhuanlan.zhihu.com/p/53660395

Backbone Can Not be Trained at Once: Rolling Back to Pre-trained Network for Person Re-Identification

• intro: AAAI 2019
• intro: Seoul National University & Samsung SDS
• arxiv: https://arxiv.org/abs/1901.06140

Ensemble Feature for Person Re-Identification

• keywords: EnsembleNet
• arxiv: https://arxiv.org/abs/1901.05798

Adversarial Metric Attack for Person Re-identification

• intro: University of Oxford & Johns Hopkins University
• arxiv: https://arxiv.org/abs/1901.10650

Discovering Underlying Person Structure Pattern with Relative Local Distance for Person Re-identification

• intro: SYSU
• arxiv: https://arxiv.org/abs/1901.10100
• github: https://github.com/Wanggcong/RLD_codes

Attributes-aided Part Detection and Refinement for Person Re-identification

https://arxiv.org/abs/1902.10528

Bags of Tricks and A Strong Baseline for Deep Person Re-identification

• intro: CVPR 2019 Workshop
• arxiv: https://arxiv.org/abs/1903.07071
• paper: http://openaccess.thecvf.com/content_CVPRW_2019/papers/TRMTMCT/Luo_Bag_of_Tricks_and_a_Strong_Baseline_for_Deep_Person_CVPRW_2019_paper.pdf
• slides: https://drive.google.com/file/d/1h9SgdJenvfoNp9PTUxPiz5_K5HFCho-V/view
• github: https://github.com/michuanhaohao/reid-strong-baseline

Auto-ReID: Searching for a Part-aware ConvNet for Person Re-Identification

• keywords: NAS
• arxiv: https://arxiv.org/abs/1903.09776
• github(official): https://github.com/D-X-Y/Auto-ReID-and-Others

Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identification

• intro: CVPR 2019
• intro: Tsinghua University & Megvii Technology
• keywords: Visibility-aware Part Model (VPM)
• arxiv: https://arxiv.org/abs/1904.00537

Pedestrian re-identification based on Tree branch network with local and global learning

• intro: ICME 2019 oral
• arxiv: https://arxiv.org/abs/1904.00355

Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification

• intro: CVPR 2019
• arxiv: https://arxiv.org/abs/1904.01990
• github: https://github.com/zhunzhong07/ECN

Person Re-identification with Bias-controlled Adversarial Training

https://arxiv.org/abs/1904.00244

Relation-Aware Global Attention for Person Re-identification

• intro: CVPR 2020
• intro: University of Science and Technology of China & Microsoft Research Asia
• arxiv: https://arxiv.org/abs/1904.02998
• github: https://github.com/microsoft/Relation-Aware-Global-Attention-Networks

Person Re-identification with Metric Learning using Privileged Information

• intro: IEEE TIP
• arxiv: https://arxiv.org/abs/1904.05005

Multi-Scale Body-Part Mask Guided Attention for Person Re-identification

• intro: Suning R&D Center USA
• arxiv: https://arxiv.org/abs/1904.11041

Deep Constrained Dominant Sets for Person Re-identification

https://arxiv.org/abs/1904.11397

Illumination-Adaptive Person Re-identification

• intro: 1The University of Tokyo & National Taiwan University & National Institute of Informatics
• arxiv: https://arxiv.org/abs/1905.04525

Domain Adaptive Person Re-Identification via Camera Style Generation and Label Propagation

• intro: Sun Yat-Sen University & Chinese Academy of Sciences
• arxiv: https://arxiv.org/abs/1905.05382

Beyond Intra-modality Discrepancy: A Comprehensive Survey of Heterogeneous Person Re-identification

https://arxiv.org/abs/1905.10048

Deep Multi-Index Hashing for Person Re-Identification

• intro: Nanjing University
• arxiv: https://arxiv.org/abs/1905.10980

Attention: A Big Surprise for Cross-Domain Person Re-Identification

https://arxiv.org/abs/1905.12830

Semantics-Aligned Representation Learning for Person Re-identification

• intro: USTC & MSRA
• keywords: Semantics Aligning Network (SAN)
• arxiv: https://arxiv.org/abs/1905.13143

Rethinking Person Re-Identification with Confidence

• intro: EPFL
• arxiv: https://arxiv.org/abs/1906.04692

CDPM: Convolutional Deformable Part Models for Person Re-identification

https://arxiv.org/abs/1906.04976

Resolution-invariant Person Re-Identification

• intro: IJCAI 2019
• intro: Peking University & Horizon Robotics
• arxiv: https://arxiv.org/abs/1906.09748

Interaction-and-Aggregation Network for Person Re-identification

• intro: CVPR 2019
• arxiv: https://arxiv.org/abs/1907.08435

Distilled Person Re-identification: Towards a More Scalable System

• intro: CVPR 2019
• intro: Sun Yat-sen University & YouTu Lab, Tencent
• keywords: Multi-teacher Adaptive Similarity Distillation Framework, Log-Euclidean Similarity Distillation Loss, Adaptive Knowledge Aggregator
• paper: http://openaccess.thecvf.com/content_CVPR_2019/papers/Wu_Distilled_Person_Re-Identification_Towards_a_More_Scalable_System_CVPR_2019_paper.pdf

Universal Person Re-Identification

• intro: Queen Mary University of London & Vision Semantics Ltd.
• arxiv: https://arxiv.org/abs/1907.09511

ABD-Net: Attentive but Diverse Person Re-Identification

• intro: ICCV 2019
• arxiv: https://arxiv.org/abs/1908.01114
• github: https://github.com/TAMU-VITA/ABD-Net

Fairest of Them All: Establishing a Strong Baseline for Cross-Domain Person ReID

• intro: University of Waterloo & SPORTLOGiQ Inc.
• arxiv: https://arxiv.org/abs/1907.12016

Progressive Cross-camera Soft-label Learning for Semi-supervised Person Re-identification

https://arxiv.org/abs/1908.05669

Mixed High-Order Attention Network for Person Re-Identification

• intro: ICCV 2019
• arxiv: https://arxiv.org/abs/1908.05819
• github: https://github.com/chenbinghui1/MHN

Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification

• intro: ICCV 2019
• arxiv: https://arxiv.org/abs/1908.06052

HorNet: A Hierarchical Offshoot Recurrent Network for Improving Person Re-ID via Image Captioning

• intro: IJCAI 2019
• intro: Nanjing Institute of Advanced Artificial Intelligence & Horizon Robotics
• arxiv: https://arxiv.org/abs/1908.04915

Temporal Knowledge Propagation for Image-to-Video Person Re-identification

• intro: ICCV 2019
• arxiv: https://arxiv.org/abs/1908.03885

SBSGAN: Suppression of Inter-Domain Background Shift for Person Re-Identification

• intro: ICCV 2019
• arxiv: https://arxiv.org/abs/1908.09086

Learning Deep Representations by Mutual Information for Person Re-identification

https://arxiv.org/abs/1908.05860

Orthogonal Center Learning with Subspace Masking for Person Re-Identification

• intro: Youtu X-lab, Tencent
• arxiv: https://arxiv.org/abs/1908.10535

Adaptive Graph Representation Learning for Video Person Re-identification

https://arxiv.org/abs/1909.02240

POD: Practical Object Detection with Scale-Sensitive Network

https://arxiv.org/abs/1909.02225

Second-order Non-local Attention Networks for Person Re-identification

• intro: ICCV 2019
• arxiv: https://arxiv.org/abs/1909.00295

Cross-Dataset Person Re-Identification via Unsupervised Pose Disentanglement and Adaptation

• intro: ICCV 2019
• arxiv: https://arxiv.org/abs/1909.09675

View Confusion Feature Learning for Person Re-identification

• intro: ICCV 2019
• arxiv: https://arxiv.org/abs/1910.03849

Augmented Hard Example Mining for Generalizable Person Re-Identification

https://arxiv.org/abs/1910.05280

Learning Generalisable Omni-Scale Representations for Person Re-Identification

• arxiv: https://arxiv.org/abs/1910.06827
• github: https://github.com/KaiyangZhou/deep-person-reid

Attention Network Robustification for Person ReID

• intro: DAMO Academy, Alibaba Group
• arxiv: https://arxiv.org/abs/1910.07038

Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification

• intro: ICCV 2019
• keywords: dual part-aligned block (DPB)
• arxiv: https://arxiv.org/abs/1910.10111
• github: https://github.com/ggjy/P2Net.pytorch

An End-to-End Foreground-Aware Network for Person Re-Identification

https://arxiv.org/abs/1910.11547

Learning Disentangled Representation for Robust Person Re-identification

• intro: NeurIPS 2019
• keywords: identity shuffle GAN (IS-GAN)
• project page: https://cvlab.yonsei.ac.kr/projects/ISGAN/
• arxiv: https://arxiv.org/abs/1910.12003

ID-aware Quality for Set-based Person Re-identification

https://arxiv.org/abs/1911.09143

Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification

• intro: WACV 2020
• arxiv: https://arxiv.org/abs/1911.11314

Collaborative Attention Network for Person Re-identification

https://arxiv.org/abs/1911.13008

Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification

• intro: AAAI 2020
• arxiv: https://arxiv.org/abs/1912.01300
• github: https://github.com/zzhsysu/VA-ReID

AANet: Attribute Attention Network for Person Re-Identifications

• intro: CVPR 2019
• arxiv: https://arxiv.org/abs/1912.09021

In Defense of the Triplet Loss Again: Learning Robust Person Re-Identification with Fast Approximated Triplet Loss and Label Distillation

• arxiv: https://arxiv.org/abs/1912.07863
• github: https://github.com/TAMU-VITA/FAT

Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch Normalization

• intro: ECCV 2020
• intro: Tsinghua University & Huawei Inc. & Hefei University of Technology & University of Science and Technology of China
• arxiv: https://arxiv.org/abs/2001.08680
• github: https://github.com/automan000/Camera-based-Person-ReID

Intra-Camera Supervised Person Re-Identification

https://arxiv.org/abs/2002.05046

Towards Precise Intra-camera Supervised Person Re-identification

• intro: Zhejiang University & Alibaba Group
• arxiv: https://arxiv.org/abs/2002.04932

Diversity-Achieving Slow-DropBlock Network for Person Re-Identification

https://arxiv.org/abs/2002.04414

MagnifierNet: Towards Semantic Regularization and Fusion for Person Re-identification

https://arxiv.org/abs/2002.10979

Triplet Online Instance Matching Loss for Person Re-identification

https://arxiv.org/abs/2002.10560

When Person Re-identification Meets Changing Clothes

https://arxiv.org/abs/2003.04070

Multi-task Learning with Coarse Priors for Robust Part-aware Person Re-identification

• intro: South China University of Technolog & University of Sydney
• keywords: Multi-task Part-aware Network (MPN)
• arxiv: https://arxiv.org/abs/2003.08069

Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking

• intro: CVPR 2020
• intro: To attack ReID, we propose a learning-to-mis-rank formulation to perturb the ranking of the system output
• arxiv: https://arxiv.org/abs/2004.04199
• github: https://github.com/whj363636/Adversarial-attack-on-Person-ReID-With-Deep-Mis-Ranking

Real-world Person Re-Identification via Degradation Invariance Learning

• intro: CVPR 2020
• arxiv: https://arxiv.org/abs/2004.04933

Person Re-identification in the 3D Space

• intro: University of Technology Sydney
• arxiv: https://arxiv.org/abs/2006.04569
• github(official): https://github.com/layumi/person-reid-3d

Rethinking Classification Loss Designs for Person Re-identification with a Unified View

• intro: University of Science and Technology of China & MicroSoft Research Asia & Columbia University
• arxiv: https://arxiv.org/abs/2006.04991

Multiple Expert Brainstorming for Domain Adaptive Person Re-identification

• intro: ECCV 2020
• arxiv: https://arxiv.org/abs/2007.01546
• github: https://github.com/YunpengZhai/MEB-Net

ESA-ReID: Entropy-Based Semantic Feature Alignment for Person re-ID

• intro: Alibaba Group
• arxiv: https://arxiv.org/abs/2007.04644

Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification

• intro: ECCV 2020 oral
• intro: Carnegie Mellon University & NVIDIA
• arxiv: https://arxiv.org/abs/2007.10315

Dual Distribution Alignment Network for Generalizable Person Re-Identification

https://arxiv.org/abs/2007.13249

Hierarchical Bi-Directional Feature Perception Network for Person Re-Identification

• intro: ACM MM 2020
• arxiv: https://arxiv.org/abs/2008.03509

Black Re-ID: A Head-shoulder Descriptor for the Challenging Problem of Person Re-Identification

• arxiv: https://arxiv.org/abs/2008.08528
• github: https://github.com/xbq1994/HAA

Faster Person Re-Identification

• intro: ECCV 2020
• arxiv: https://arxiv.org/abs/2008.06826
• github: https://github.com/wangguanan/light-reid

Do Not Disturb Me: Person Re-identification Under the Interference of Other Pedestrians

• intro: ECCV 2020
• arxiv: https://arxiv.org/abs/2008.06963
• github(official): https://github.com/X-BrainLab/PI-ReID

Apparel-invariant Feature Learning for Apparel-changed Person Re-identification

https://arxiv.org/abs/2008.06181

Cluster-level Feature Alignment for Person Re-identification

https://arxiv.org/abs/2008.06810

Self-Supervised Gait Encoding with Locality-Aware Attention for Person Re-Identification

• intro: IJCAI 2020
• arxiv: https://arxiv.org/abs/2008.09435
• github: https://github.com/Kali-Hac/SGE-LA

Receptive Multi-granularity Representation for Person Re-Identification

• intro: Championship solution of NAIC 2019 Person re-ID Track
• arxiv: https://arxiv.org/abs/2008.13450

Proxy Task Learning For Cross-Domain Person Re-Identification

• intro: ICME 2020
• paper: https://scihub.wikicn.top/10.1109/ICME46284.2020.9102898
• paper: https://ieeexplore.ieee.org/document/9102898
• github: https://github.com/huanghoujing/PTL

Progressive Bilateral-Context Driven Model for Post-Processing Person Re-Identification

• arxiv: https://arxiv.org/abs/2009.03098
• github: https://github.com/123ci/PBCmodel

Devil’s in the Detail: Graph-based Key-point Alignment and Embedding for Person Re-ID

• intro: Tencent Youtu Lab & Sun Yat-sen University & Huazhong University of Science and Technology
• arxiv: https://arxiv.org/abs/2009.05250

Hybrid-Attention Guided Network with Multiple Resolution Features for Person Re-Identification

• arxiv: https://arxiv.org/abs/2009.07536
• github: https://github.com/libraflower/MutipleFeature-for-PRID

Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss

https://arxiv.org/abs/2009.10295

Batch Coherence-Driven Network for Part-aware Person Re-Identification

https://arxiv.org/abs/2009.09692

FTN: Foreground-Guided Texture-Focused Person Re-Identification

https://arxiv.org/abs/2009.11425

Improve Person Re-Identification With Part Awareness Learning

• intro: TIP 2020
• intro: Institute of Automation, Chinese Academy of Sciences & Horizon Robotics, Inc
• paper: https://ieeexplore.ieee.org/document/9124699
• github: https://github.com/huanghoujing/PAL-MGN

Performance Optimization for Federated Person Re-identification via Benchmark Analysis

• intro: ACMMM 2020
• arxiv: https://arxiv.org/abs/2008.11560

DomainMix: Learning Generalizable Person Re-Identification Without Human Annotations

https://arxiv.org/abs/2011.11953

Multi-Domain Adversarial Feature Generalization for Person Re-Identification

https://arxiv.org/abs/2011.12563

Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification

https://arxiv.org/abs/2012.00417

Unsupervised Pre-training for Person Re-identification

• intro: University of Science and Technology of China & Microsoft Research
• intro: LUPerson dataset
• arxiv: https://arxiv.org/abs/2012.03753

UnrealPerson: An Adaptive Pipeline towards Costless Person Re-identification

• arxov: https://arxiv.org/abs/2012.04268
• github: https://github.com/FlyHighest/UnrealPerson

One for More: Selecting Generalizable Samples for Generalizable ReID Model

• intro: Tencent Youtu Lab & Sun Yat-sen University & Southern University of Science and Technology
• arxiv: https://arxiv.org/abs/2012.05475

Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification

• intro: AAAI 2021
• arxiv: https://arxiv.org/abs/2012.08733

Camera-aware Proxies for Unsupervised Person Re-Identification

• intro: AAAI 2021
• intro: 1Zhejiang University & Alibaba Group
• arxiv: https://arxiv.org/abs/2012.10674

1st Place Solution to VisDA-2020: Bias Elimination for Domain Adaptive Pedestrian Re-identification

• intro: 1st place solution to VisDA-2020 Challenge (ECCVW 2020)
• intro: Zhejiang University & Alibaba Group
• project page: http://ai.bu.edu/visda-2020/
• arxiv: https://arxiv.org/abs/2012.13498
• github: https://github.com/vimar-gu/Bias-Eliminate-DA-ReID

HAVANA: Hierarchical and Variation-Normalized Autoencoder for Person Re-identification

https://arxiv.org/abs/2101.02568

AXM-Net: Cross-Modal Context Sharing Attention Network for Person Re-ID

https://arxiv.org/abs/2101.08238

TransReID: Transformer-based Object Re-Identification

• intro: Alibaba Group & Zhejiang University
• arxiv: https://arxiv.org/abs/2102.04378

Deep Miner: A Deep and Multi-branch Network which Mines Rich and Diverse Features for Person Re-identification

• intro: Digeiz AI Lab & Ecole Polytechnique
• arxiv: https://arxiv.org/abs/2102.09321

AttriMeter: An Attribute-guided Metric Interpreter for Person Re-Identification

• intro: University of Science and Technology of China & JD AI Research & Ryerson University
• arxiv: https://arxiv.org/abs/2103.01451

Watching You: Global-guided Reciprocal Learning for Video-based Person Re-identification

• intro: CVPR 2021
• arxiv: https://arxiv.org/abs/2103.04337

Lifelong Person Re-Identification via Adaptive Knowledge Accumulation

• intro: CVPR 2021
• arxiv: https://arxiv.org/abs/2103.12462

Spatiotemporal Transformer for Video-based Person Re-identification

• intro: Beihang University & Pengcheng Laboratory & Tsinghua University & University of Science and Technology of China & Xidian University
• arxiv: https://arxiv.org/abs/2103.16469

AAformer: Auto-Aligned Transformer for Person Re-Identification

• intro: Chinese Academy of Sciences & Peng Cheng Laboratory & Peking University & Alibaba Group
• arxiv: https://arxiv.org/abs/2104.00921

Combined Depth Space based Architecture Search For Person Re-identification

• intro: CVPR 2021
• arxiv: https://arxiv.org/abs/2104.04163

Graph-based Person Signature for Person Re-Identifications

• intro: CVPR 2021 Workshops
• arxiv: https://arxiv.org/abs/2104.06770

Unsupervised Multi-Source Domain Adaptation for Person Re-Identification

• intro: CVPR 2021 oral
• arxiv: https://arxiv.org/abs/2104.12961

Generalizable Person Re-identification with Relevance-aware Mixture of Experts

• intro: CVPR 2021
• arxiv: https://arxiv.org/abs/2105.09156

Transformer-Based Deep Image Matching for Generalizable Person Re-identification

https://arxiv.org/abs/2105.14432

Person Re-Identification with a Locally Aware Transformer

• intro: University of Maryland Baltimore County
• arxiv: https://arxiv.org/abs/2106.03720

Learning Instance-level Spatial-Temporal Patterns for Person Re-identification

• intro: ICCV 2021
• arxiv: https://arxiv.org/abs/2108.00171
• github: https://github.com/RenMin1991/cleaned-DukeMTMC-reID/

IDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID

• intro: ICCV 2021 oral
• keywords: Peking University & Singapore University of Technology and Design & Megvii Technology & National University of Singapore & Peng Cheng Laboratory
• arxiv: https://arxiv.org/abs/2108.02413
• github: https://github.com/SikaStar/IDM

Benchmarks for Corruption Invariant Person Re-identification

• intro: NeurIPS 2021 Track on Datasets and Benchmarks
• arxiv: https://arxiv.org/abs/2111.00880
• github: https://github.com/MinghuiChen43/CIL-ReID

Self-Supervised Pre-Training for Transformer-Based Person Re-Identification

• intro: Alibaba Group
• arxiv: https://arxiv.org/abs/2111.12084
• github: https://github.com/michuanhaohao/TransReID-SSL

Stronger Baseline for Person Re-Identification

• intro: The third-place solution for ICCV2021 VIPriors Re-identification Challenge
• arxiv: https://arxiv.org/abs/2112.01059

Dual Cluster Contrastive learning for Person Re-Identification

• intro: Institute of Automation, CAS
• arxiv: https://arxiv.org/abs/2112.04662
• github: https://github.com/htyao89/Dual-Cluster-Contrastive/

META: Mimicking Embedding via oThers’ Aggregation for Generalizable Person Re-identification

• intro: CASIA & UCAS & JD AI Reasearch
• arxiv: https://arxiv.org/abs/2112.08684

Multi-Centroid Representation Network for Domain Adaptive Person Re-ID

• intro: AAAI 2022
• arxiv: https://arxiv.org/abs/2112.11689

Camera-Conditioned Stable Feature Generation for Isolated Camera Supervised Person Re-IDentification

• intro: CVPR 2022
• arxiv: https://arxiv.org/abs/2203.15210

Large-Scale Pre-training for Person Re-identification with Noisy Labels

• intro: CVPR 2022
• intro: University of Science and Technology of China & Microsoft Research & Microsoft Cloud AI & IDEA
• arxiv: https://arxiv.org/abs/2203.16533
• github: https://github.com/DengpanFu/LUPerson-NL

A Free Lunch to Person Re-identification: Learning from Automatically Generated Noisy Tracklets

• intro: Tsinghua University & Alibaba Group
• arxiv: https://arxiv.org/abs/2204.00891

Clothes-Changing Person Re-identification with RGB Modality Only

• intro: CVPR 2022
• arxiv: https://arxiv.org/abs/2204.06890
• github: https://github.com/guxinqian/Simple-CCReID

NFormer: Robust Person Re-identification with Neighbor Transformer

• intro: CVPR 2022 poster
• arxiv: https://arxiv.org/abs/2204.09331
• github: https://github.com/haochenheheda/NFormer

Feature-Distribution Perturbation and Calibration for Generalized Person ReID

• iintro: Queen Mary University of London
• arxiv: https://arxiv.org/abs/2205.11197

Person Search

End-to-End Deep Learning for Person Search

• arxiv: https://arxiv.org/abs/1604.01850v1
• paper: http://www.ee.cuhk.edu.hk/~xgwang/PS/paper.pdf

Joint Detection and Identification Feature Learning for Person Search

• intro: CVPR 2017 Spotlight
• intro: The Chinese University of Hong Kong & Sun Yat-Sen University & SenseTime Group Limited
• 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
• intro: University of Technology Sydney & UTSA & USTC & UCSD
• 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

• intro: Xi’an Jiaotong-Liverpool University & National University of Singapore
• arxiv: https://arxiv.org/abs/1705.05552

Neural Person Search Machines

• intro: ICCV 2017
• intro: Hefei University of Technology & National University of Singapore & Tencent AI Lab & Panasonic R&D Center Singapore & Southwest Jiaotong University & 360 AI Institute
• arxiv: https://arxiv.org/abs/1707.06777
• paper: https://ai.tencent.com/ailab/media/publications/Neural_Person_Search_Machines.pdf

Efficient Person Search via Expert-Guided Knowledge Distillation

• paper: https://ieeexplore.ieee.org/document/8759990

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

• intro: Chongqing University & Hefei University of Technology
• keywords: I-Net
• arxiv: https://arxiv.org/abs/1804.00376

Person Search via A Mask-guided Two-stream CNN Model

• intro: ECCV 2018
• intro: Nanjing University of Science and Technology & Youtu Lab, Tencent
• arxiv: https://arxiv.org/abs/1807.08107

Person Search by Multi-Scale Matching

• intro: ECCV 2018
• intro: Queen Mary University of London & Vision Semantics Ltd
• keywords: Cross-Level Semantic Alignment (CLSA)
• arxiv: https://arxiv.org/abs/1807.08582

RCAA: Relational Context-Aware Agents for Person Search

• intro: ECCV 2018
• intro: Carnegie Mellon University & Chinese Academy of Sciences & University of Technology Sydney
• paper: http://openaccess.thecvf.com/content_ECCV_2018/papers/Xiaojun_Chang_RCAA_Relational_Context-Aware_ECCV_2018_paper.pdf

Fast Person Search Pipeline

• intro: ICME 2019
• intro: Sun Yat-sen University
• paper: https://ieeexplore.ieee.org/abstract/document/8784982/
• paper: https://sci-hub.tw/10.1109/ICME.2019.00195

Learning Context Graph for Person Search

• intro: CVPR 2019 Oral
• intro: Shanghai Jiao Tong University & Tencent YouTu Lab & Inception Institute of Artificial Intelligence, UAE
• arxiv: https://arxiv.org/abs/1904.01830
• github(official, Pytorch): https://github.com/sjtuzq/person_search_gcn

Query-guided End-to-End Person Search

• intro: CVPR 2019 poster
• intro: OSRAM GmbH & Technische Universität München
• keywords: query-guided end-to-end person search network (QEEPS)
• arxiv: https://arxiv.org/abs/1905.01203
• github(official): https://github.com/munjalbharti/Query-guided-End-to-End-Person-Search

Knowledge Distillation for End-to-End Person Search

• intro: BMVC 2019
• intro: Technische Universität München & OSRAM GmbH
• arxiv: https://arxiv.org/abs/1909.01058

Re-ID Driven Localization Refinement for Person Search

• intro: ICCV 2019
• intro: Huazhong University of Science and Technology & Peking University & Shanghai Jiao Tong University & Megvii Technology
• arxiv: https://arxiv.org/abs/1909.08580

End-to-End Thorough Body Perception for Person Search

• intro: AAAI 2020
• intro: Horizon Robotics & Chinese Academy of Sciences
• paper: https://aaai.org/Papers/AAAI/2020GB/AAAI-TianK.2778.pdf

Hierarchical Online Instance Matching for Person Search

• intro: AAAI 2020
• paper: https://aaai.org/Papers/AAAI/2020GB/AAAI-ChenD.1557.pdf
• github: https://github.com/DeanChan/HOIM-PyTorch

Robust Partial Matching for Person Search in the Wild

• intro: CVPR 2020
• intro: Peking University & Intellifusion & CUHK
• keywords: Align-to-Part Network (APNet)
• arxiv: https://arxiv.org/abs/2004.09329

Joint Person Objectness and Repulsion for Person Search

• intro: Chinese Academy of Sciences
• aarxiv: https://arxiv.org/abs/2006.00155

Norm-Aware Embedding for Efficient Person Search

• intro: CVPR 2020
• paper: http://openaccess.thecvf.com/content_CVPR_2020/papers/Chen_Norm-Aware_Embedding_for_Efficient_Person_Search_CVPR_2020_paper.pdf
• arxiv: https://github.com/DeanChan/NAE4PS

A Multi-task Joint Framework for Real-time Person Search

https://arxiv.org/abs/2012.06418

Diverse Knowledge Distillation for End-to-End Person Search

• intro: AAAI 2021
• intro: Tongji University & The University of Adelaide & Monash University
• arxiv: https://arxiv.org/abs/2012.11187
• github: https://github.com/zhangxinyu-xyz/DKD-PersonSearch

Multi-Attribute Enhancement Network for Person Search

• arxiv: https://arxiv.org/abs/2102.07968
• gihtub: https://github.com/chenlq123/MAE

Sequential End-to-end Network for Efficient Person Search

• intro: Tongji University
• arxiv: https://arxiv.org/abs/2103.10148

Anchor-Free Person Search

• intro: CVPR 2021
• intro: Inception Institute of Artificial Intelligence (IIAI) & University of Oxford
• arxiv: https://arxiv.org/abs/2103.11617
• github: https://github.com/daodaofr/AlignPS

Exploring Visual Context for Weakly Supervised Person Search

• arxiv: https://arxiv.org/abs/2106.10506
• github: https://github.com/ljpadam/CGPS

Making Person Search Enjoy the Merits of Person Re-identification

• intro: Shanghai Jiao Tong University
• arxiv: https://arxiv.org/abs/2108.10536

Context-Aware Unsupervised Clustering for Person Search

https://arxiv.org/abs/2110.01341

Learning Context-Aware Embedding for Person Search

• intro: Beihang University & MEGVII Technology
• arxiv: https://arxiv.org/abs/2111.14316

Subtask-dominated Transfer Learning for Long-tail Person Search

• intro: Shanghai Jiao Tong University
• arxiv: https://arxiv.org/abs/2112.00527

Global-Local Context Network for Person Search

• arxiv: https://arxiv.org/abs/2112.02500
• github: https://github.com/ZhengPeng7/GLCNet

Cascade Transformers for End-to-End Person Search

• intro: CVPR 2022
• arxiv: https://arxiv.org/abs/2203.09642
• github: https://github.com/Kitware/COAT

CGUA: Context-Guided and Unpaired-Assisted Weakly Supervised Person Search

https://arxiv.org/abs/2203.14307

PSTR: End-to-End One-Step Person Search With Transformers

• intro: CVPR 2022
• arxiv: https://arxiv.org/abs/2204.03340
• github: https://github.com/JialeCao001/PSTR

OIMNet++: Prototypical Normalization and Localization-aware Learning for Person Search

• intro: ECCV 2022
• intro: Yonsei University & Korea Institute of Science and Technology
• project page: https://cvlab.yonsei.ac.kr/projects/OIMNetPlus/
• arxiv: https://arxiv.org/abs/2207.10320
• github: https://github.com/cvlab-yonsei/OIMNetPlus

Domain Adaptive Person Search

• intro: ECCV 2022 Oral
• intro: Shanghai Jiao Tong University & Tencent Youtu Lab
• arxiv: https://arxiv.org/abs/2207.11898
• github: https://github.com/caposerenity/DAPS

Pose / Viewpoint for Re-ID

Pose Invariant Embedding for Deep Person Re-identification

• keywords: pose invariant embedding (PIE), PoseBox fusion (PBF) CNN
• arixv: 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

• intro: ICCV 2017
• arxiv: 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
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Pose_Transferrable_Person_CVPR_2018_paper.pdf

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(official, Matlab): https://github.com/layumi/Person-reID_GAN
• github: https://github.com/qiaoguan/Person-reid-GAN-pytorch

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

• intro: CVPR 2018 spotlight
• intro: PTGAN
• arxiv: https://arxiv.org/abs/1711.08565
• github: https://github.com/JoinWei-PKU/PTGAN

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

• arxiv: https://arxiv.org/abs/1801.06742
• github: https://github.com/Huang-3/MpRL-for-person-re-ID

Joint Discriminative and Generative Learning for Person Re-identification

• intro: CVPR 2019 oral
• intro: NVIDIA & University of Technology Sydney & Australian National University
• arxiv: https://arxiv.org/abs/1904.07223
• github: https://github.com/NVlabs/DG-Net
• youtube: https://www.youtube.com/watch?v=ubCrEAIpQs4
• bilibili: https://www.bilibili.com/video/av51439240

Human Parsing for Re-ID

Human Semantic Parsing for Person Re-identification

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

Improved Person Re-Identification Based on Saliency and Semantic Parsing with Deep Neural Network Models

• keywords: Saliency-Semantic Parsing Re-Identification (SSP-ReID)
• arxiv: https://arxiv.org/abs/1807.05618

Identity-Guided Human Semantic Parsing for Person Re-Identification

• intro: ECCV 2020 spotlight
• arxiv: https://arxiv.org/abs/2007.13467
• github: https://github.com/CASIA-IVA-Lab/ISP-reID

Human Parsing Based Alignment with Multi-task Learning for Occluded Person Re-identification

• intro: ICME 2020 Oral
• paper; https://scihub.wikicn.top/10.1109/ICME46284.2020.9102789
• paper: https://ieeexplore.ieee.org/abstract/document/9102789
• github: https://github.com/huanghoujing/HPNet

Occluded Person Re-ID / Partial Person Re-ID

Partial Person Re-identification

• intro: ICCV 2015
• arxiv: https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Zheng_Partial_Person_Re-Identification_ICCV_2015_paper.pdf

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

• intro: CVPR 2018
• intro: Market1501 rank1=83.58%
• keywords: Deep Spatial feature Reconstruction (DSR)
• arxiv: https://arxiv.org/abs/1801.00881
• github(official, PyTorch): https://github.com/lingxiao-he/Partial-Person-ReID

Occluded Person Re-identification

• intro: ICME 2018
• intro: Sun Yat-Sen University
• arxiv: https://arxiv.org/abs/1804.02792

Partial Person Re-identification with Alignment and Hallucination

• intro: Imperial College London
• keywords: Partial Matching Net (PMN)
• arxiv: https://arxiv.org/abs/1807.09162

SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and Partial Person Re-Identification

• intro: ACCV 2018
• intro: Megvii Inc. (Face++) & Chinese Academy of Sciences
• arxiv: https://arxiv.org/abs/1810.06996
• github: https://github.com/xfanplus/Open-SCPNet

STNReID : Deep Convolutional Networks with Pairwise Spatial Transformer Networks for Partial Person Re-identification

• intro: Zhejiang University & Megvii Inc
• arxiv: https://arxiv.org/abs/1903.07072

Foreground-aware Pyramid Reconstruction for Alignment-free Occluded Person Re-identification

https://arxiv.org/abs/1904.04975

A Novel Teacher-Student Learning Framework For Occluded Person Re-Identification

https://arxiv.org/abs/1907.03253

VRSTC: Occlusion-Free Video Person Re-Identification

• intro: CVPR 2019
• arxiv: https://arxiv.org/abs/1907.08427

Pose-Guided Feature Alignment for Occluded Person Re-Identification

• intro: ICCV 2019
• intro: Baidu Research & University of Technology Sydney
• keywords: Pose-Guided Feature Alignment (PGFA)
• paper: http://openaccess.thecvf.com/content_ICCV_2019/papers/Miao_Pose-Guided_Feature_Alignment_for_Occluded_Person_Re-Identification_ICCV_2019_paper.pdf
• paper: https://yu-wu.net/pdf/ICCV2019_Occluded-reID.pdf
• github: https://github.com/lightas/Occluded-DukeMTMC-Dataset

High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification

• intro: CVPR 2020
• intro: Institute of Automation, CAS & Megvii Inc. & Beijing Institute of Technology
• arxiv: https://arxiv.org/abs/2003.08177
• github: https://github.com/wangguanan/HOReID

Pose-guided Visible Part Matching for Occluded Person ReID

• intro: CVPR 2020
• intro: Dalian University of Technology & Pengcheng Lab & The University of Sydney
• arxiv: https://arxiv.org/abs/2004.00230
• github(official, pytorch): https://github.com/hh23333/PVPM

MHSA-Net: Multi-Head Self-Attention Network for Occluded Person Re-Identification

• arxiv: https://arxiv.org/abs/2008.04015
• github: https://github.com/hongchenphd/MHSA-Net

Holistic Guidance for Occluded Person Re-Identification

• intro: École de technologie supérieure & Genetec Inc
• arxiv: https://arxiv.org/abs/2104.06524

Neighbourhood-guided Feature Reconstruction for Occluded Person Re-Identification

https://arxiv.org/abs/2105.07345

Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer

• intro: CVPR 2021
• arxiv: https://arxiv.org/abs/2106.04095

Feature Completion for Occluded Person Re-Identification

• intro: TPAMI
• arxiv: https://arxiv.org/abs/2106.12733
• github: https://github.com/blue-blue272/OccludedReID-RFCnet

Learning Disentangled Representation Implicitly via Transformer for Occluded Person Re-Identification

• arxiv: https://arxiv.org/abs/2107.02380
• github: https://github.com/Anonymous-release-code/DRL-Net

Pose-Guided Feature Learning with Knowledge Distillation for Occluded Person Re-Identification

• intro: ACM MM 2021
• arxiv: https://arxiv.org/abs/2108.00139

Feature Erasing and Diffusion Network for Occluded Person Re-Identification

• intro: Monash University & SenseTime & The University of Sydney & Xidian University
• arxiv: https://arxiv.org/abs/2112.08740

Quality-aware Part Models for Occluded Person Re-identification

• intro: South China University of Technology & Baidu Inc & Shenzhen University & JD Explore Academy
• arxiv: https://arxiv.org/abs/2201.00107

Motion-Aware Transformer For Occluded Person Re-identification

• intro: NetEase & China JiLiang University & Hunan Institute of Engineering
• arxiv: https://arxiv.org/abs/2202.04243

Cross-modality Re-ID

RGB-IR Re-ID

RGB-Infrared Cross-Modality Person Re-Identification

• intro: ICCV 2017
• paper: http://openaccess.thecvf.com/content_ICCV_2017/papers/Wu_RGB-Infrared_Cross-Modality_Person_ICCV_2017_paper.pdf

RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment

• intro: ICCV 2019
• keywords: Alignment Generative Adversarial Network (AlignGAN)
• arxiv: https://arxiv.org/abs/1910.05839

Learning by Aligning: Visible-Infrared Person Re-identification using Cross-Modal Correspondences

• intro: ICCV 2021
• intro: Yonsei University
• project page: https://cvlab.yonsei.ac.kr/projects/LbA/
• arxiv: https://arxiv.org/abs/2108.07422

Depth-Based Re-ID

Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-Identification

• intro: ECCV 2018
• arxiv: http://openaccess.thecvf.com/content_ECCV_2018/papers/Nikolaos_Karianakis_Reinforced_Temporal_Attention_ECCV_2018_paper.pdf

A Cross-Modal Distillation Network for Person Re-identification in RGB-Depth

https://arxiv.org/abs/1810.11641

Low Resolution Re-ID

Multi-scale Learning for Low-resolution Person Re-identification

• intro: ICCV 2015
• arxiv: https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Li_Multi-Scale_Learning_for_ICCV_2015_paper.pdf

Cascaded SR-GAN for Scale-Adaptive Low Resolution Person Re-identification

• intro: IJCAI 2018
• arxiv: https://www.ijcai.org/proceedings/2018/0541.pdf

Deep Low-Resolution Person Re-Identification

• intro: AAAI 2018
• keywords: Super resolution and Identity joiNt learninG (SING)
• paper: http://www.eecs.qmul.ac.uk/~xiatian/papers/JiaoEtAl_2018AAAI.pdf

Reinforcement Learning for Re-ID

Deep Reinforcement Learning Attention Selection for Person Re-Identification

• 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

CA3Net: Contextual-Attentional Attribute-Appearance Network for Person Re-Identification

https://arxiv.org/abs/1811.07544

Attribute analysis with synthetic dataset for person re-identification

• intro: Shanghai Jiao Tong University
• arxiv: https://arxiv.org/abs/2006.07139

Taking A Closer Look at Synthesis: Fine-grained Attribute Analysis for Person Re-Identification

• intro: Shanghai Jiao Tong University & National University of Defense Technology
• arxiv: https://arxiv.org/abs/2010.08145

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

Learning Distributional Representation and Set Distance for Multi-shot Person Re-identification

• intro: CMU
• arxiv: https://arxiv.org/abs/1808.01119

LVreID: Person Re-Identification with Long Sequence Videos

https://arxiv.org/abs/1712.07286

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
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Video_Person_Re-Identification_CVPR_2018_paper.pdf

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

• intro: CVPR 2018
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Exploit_the_Unknown_CVPR_2018_paper.pdf

Video Person Re-Identification With Competitive Snippet-Similarity Aggregation and Co-Attentive Snippet Embedding

• intro: CVPR 2018
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Video_Person_Re-Identification_CVPR_2018_paper.pdf

Revisiting Temporal Modeling for Video-based Person ReID

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

Video Person Re-identification by Temporal Residual Learning

https://arxiv.org/abs/1802.07918

A Spatial and Temporal Features Mixture Model with Body Parts for Video-based Person Re-Identification

https://arxiv.org/abs/1807.00975

Video-based Person Re-identification via 3D Convolutional Networks and Non-local Attention

• intro: University of Science and Technology of China & University of Chinese Academy of Sciences
• arxiv: https://arxiv.org/abs/1807.05073

Spatial-Temporal Synergic Residual Learning for Video Person Re-Identification

https://arxiv.org/abs/1807.05799

SCAN: Self-and-Collaborative Attention Network for Video Person Re-identification

https://arxiv.org/abs/1807.05688

Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification

• intro: IEEE Transactions on Multimedia
• arxiv: https://arxiv.org/abs/1808.01911

STA: Spatial-Temporal Attention for Large-Scale Video-based Person Re-Identification

• intro: AAAI 2019
• arxiv: https://arxiv.org/abs/1811.04129

Multi-scale 3D Convolution Network for Video Based Person Re-Identification

• intro: AAAI 2019
• arxiv: https://arxiv.org/abs/1811.07468

Deep Active Learning for Video-based Person Re-identification

https://arxiv.org/abs/1812.05785

Spatial and Temporal Mutual Promotion for Video-based Person Re-identification

• intro: AAAI 2019
• arxiv: https://arxiv.org/abs/1812.10305

3D PersonVLAD: Learning Deep Global Representations for Video-based Person Re-identification

https://arxiv.org/abs/1812.10222

GAN-based Pose-aware Regulation for Video-based Person Re-identification

• intro: Heriot-Watt University & University of Edinburgh & Queen’s University Belfast & Anyvision
• keywords: Weighted Fusion (WF) & Weighted-Pose Regulation (WPR)
• arxiv: https://arxiv.org/abs/1903.11552

Convolutional Temporal Attention Model for Video-based Person Re-identification

• intro: ICME 2019
• arxiv: https://arxiv.org/abs/1904.04492

Video Person Re-Identification using Learned Clip Similarity Aggregation

https://arxiv.org/abs/1910.08055

Video Person Re-ID: Fantastic Techniques and Where to Find Them

• intro: AAAI 2020
• arxiv: https://arxiv.org/abs/1912.05295
• github: https://github.com/ppriyank/Video-Person-Re-ID-Fantastic-Techniques-and-Where-to-Find-Them

Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-based Person Re-identification

• intro: CVPR 2020
• intro: 1University of Science and Technology of China & Microsoft Research Asia
• arxiv: https://arxiv.org/abs/2003.12224

Appearance-Preserving 3D Convolution for Video-based Person Re-identification

• intro: ECCV 2020 Oral
• arxiv: https://arxiv.org/abs/2007.08434
• github: https://github.com/guxinqian/AP3D

Temporal Complementary Learning for Video Person Re-Identification

• intro: ECCV 2020
• arxiv: https://arxiv.org/abs/2007.09357
• github: https://github.com/blue-blue272/VideoReID-TCLNet

Reference-Aided Part-Aligned Feature Disentangling for Video Person Re-Identification

• intro: ICME 2021
• arxiv: https://arxiv.org/abs/2103.11319

Spatial-Temporal Correlation and Topology Learning for Person Re-Identification in Videos

https://arxiv.org/abs/2104.08241

BiCnet-TKS: Learning Efficient Spatial-Temporal Representation for Video Person Re-Identification

• intro: CVPR 2021
• arxiv: https://arxiv.org/abs/2104.14783

Video-based Person Re-identification without Bells and Whistles

• intro: CVPR 2021 Biometrics Workshop
• arxiv: https://arxiv.org/abs/2105.10678
• github: https://github.com/jackie840129/CF-AAN

Keypoint Message Passing for Video-based Person Re-Identification

https://arxiv.org/abs/2111.08279

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

Adaptive Re-ranking of Deep Feature for Person Re-identification

https://arxiv.org/abs/1811.08561

Graph Convolution for Re-ranking in Person Re-identification

https://arxiv.org/abs/2107.02220

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

Cross-dataset Person Re-Identification Using Similarity Preserved Generative Adversarial Networks

https://arxiv.org/abs/1806.04533

Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatial-Temporal Patterns

• intro: CVPR 2018
• arxiv: https://arxiv.org/abs/1803.07293
• github: https://github.com/ahangchen/rank-reid

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

Unsupervised Domain Adaptive Re-Identification: Theory and Practice

• intro: Wuhan University & Horizon Robotics & Huazhong Univ. of Science and Technology
• arxiv: https://arxiv.org/abs/1807.11334
• github: https://github.com/LcDog/DomainAdaptiveReID

Deep Association Learning for Unsupervised Video Person Re-identification

• intro: BMVC 2018
• arxiv: https://arxiv.org/abs/1808.07301

Support Neighbor Loss for Person Re-Identification

• intro: ACM Multimedia (ACM MM) 2018
• arxiv: https://arxiv.org/abs/1808.06030

Unsupervised Person Re-identification by Deep Learning Tracklet Association

• intro: ECCV 2018 Oral
• keywords: Tracklet Association Unsupervised Deep Learning (TAUDL)
• arxiv: https://arxiv.org/abs/1809.02874

Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification

• intro: ICCV 2019 oral
• arxiv: https://arxiv.org/abs/1811.10144
• github: https://github.com/OasisYang/SSG

Unsupervised Tracklet Person Re-Identification

• intro: TPAMI 2019
• arxiv: https://arxiv.org/abs/1903.00535
• github: https://github.com/liminxian/DukeMTMC-SI-Tracklet

Unsupervised Person Re-identification by Deep Asymmetric Metric Embedding

• intro: TPAMI
• keywords: DEep Clustering-based Asymmetric MEtric Learning (DECAMEL)
• arxiv: https://arxiv.org/abs/1901.10177
• github: https://github.com/KovenYu/DECAMEL

Unsupervised Person Re-identification by Soft Multilabel Learning

• intro: CVPR 2019 oral
• intro: Sun Yat-sen University & YouTu Lab & Queen Mary University of London
• keywords: MAR (MultilAbel Reference learning), soft multilabel-guided hard negative mining
• project page: https://kovenyu.com/publication/2019-cvpr-mar/
• arxiv: https://arxiv.org/abs/1903.06325
• github(official, Pytorch): https://github.com/KovenYu/MAR

A Bottom-up Clustering Approach to Unsupervised Person Re-identification

• intro: AAAI 2019 oral
• paper: https://vana77.github.io/vana77.github.io/images/AAAI19.pdf
• github: https://github.com/vana77/Bottom-up-Clustering-Person-Re-identification

A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification

https://arxiv.org/abs/1904.03425

Towards better Validity: Dispersion based Clustering for Unsupervised Person Re-identification

• arxiv: https://arxiv.org/abs/1906.01308
• github: https://github.com/gddingcs/Dispersion-based-Clustering

PAC-GAN: An Effective Pose Augmentation Scheme for Unsupervised Cross-View Person Re-identification

https://arxiv.org/abs/1906.01792

Adaptive Exploration for Unsupervised Person Re-Identification

• arxiv: https://arxiv.org/abs/1907.04194
• github: https://github.com/dyh127/Adaptive-Exploration-for-Unsupervised-Person-Re-Identification

Learning to Adapt Invariance in Memory for Person Re-identification

https://arxiv.org/abs/1908.00485

Consistent Cross-view Matching for Unsupervised Person Re-identification

https://arxiv.org/abs/1908.10486

Learning to Align Multi-Camera Domain for Unsupervised Video Person Re-Identification

https://arxiv.org/abs/1909.13248

Progressive Unsupervised Person Re-identification by Tracklet Association with Spatio-Temporal Regularization

https://arxiv.org/abs/1910.11560

Asymmetric Co-Teaching for Unsupervised Cross Domain Person Re-Identification

• intro: AAAI 2020
• arxiv: https://arxiv.org/abs/1912.01349
• github: https://github.com/FlyingRoastDuck/ACT_AAAI20

Memorizing Comprehensively to Learn Adaptively: Unsupervised Cross-Domain Person Re-ID with Multi-level Memory

https://arxiv.org/abs/2001.04123

Unsupervised Domain Adaptation in the Dissimilarity Space for Person Re-identification

• intro: ECCV 2020
• arxiv: https://arxiv.org/abs/2007.13890

Unsupervised Attention Based Instance Discriminative Learning for Person Re-Identification

• intro: WACV 2021
• arxiv: https://arxiv.org/abs/2011.01888

Joint Generative and Contrastive Learning for Unsupervised Person Re-identification

• arxiv: https://arxiv.org/abs/2012.09071
• github: https://github.com/chenhao2345/GCL

Joint Noise-Tolerant Learning and Meta Camera Shift Adaptation for Unsupervised Person Re-Identification

• intro: CVPR 2021
• intro: Xiamen University & University of Trento & Minjiang Universit & Minnan Normal University
• arxiv: https://arxiv.org/abs/2103.04618
• github: https://github.com/FlyingRoastDuck/MetaCam_DSCE

Cluster Contrast for Unsupervised Person Re-Identification

• intro: Alibaba A.I. Labs & Simon Fraser University
• arxiv: https://arxiv.org/abs/2103.11568
• github: https://github.com/wangguangyuan/ClusterContrast

Intra-Inter Camera Similarity for Unsupervised Person Re-Identification

• intro: CVPR 2021
• intro: Peking University
• arxiv: https://arxiv.org/abs/2103.11658

Group-aware Label Transfer for Domain Adaptive Person Re-identification

• intro: CVPR 2021
• arxiv: https://arxiv.org/abs/2103.12366

Large-Scale Unsupervised Person Re-Identification with Contrastive Learning

• intro: Tongji University
• arxiv: https://arxiv.org/abs/2105.07914

Cluster-guided Asymmetric Contrastive Learning for Unsupervised Person Re-Identification

• intro: Beijing University of Posts and Telecommunications
• arxiv: https://arxiv.org/abs/2106.07846

Towards Discriminative Representation Learning for Unsupervised Person Re-identification

• intro: ICCV 2021
• arxiv: https://arxiv.org/abs/2108.03439

Unleashing the Potential of Unsupervised Pre-Training with Intra-Identity Regularization for Person Re-Identification

• intro: University of Science and Technology of China
• keywords: UP-ReID
• arxiv: https://arxiv.org/abs/2112.00317
• github: https://github.com/Frost-Yang-99/UP-ReID

Part-based Pseudo Label Refinement for Unsupervised Person Re-identification

• intro: CVPR 2022
• intro: KAIST
• arxiv: https://arxiv.org/abs/2203.14675

Implicit Sample Extension for Unsupervised Person Re-Identification

• intro: CVPR 2022
• arxiv: https://arxiv.org/abs/2204.06892
• github: https://github.com/PaddlePaddle/PaddleClas

Weakly Supervised Person Re-identification

Weakly Supervised Person Re-Identification

• intro: CVPR 2019
• keywords: multi-instance multi-label learning (MIML), Cross-View MIML (CV-MIML)
• arxiv: https://arxiv.org/abs/1904.03832

Weakly Supervised Person Re-identification: Cost-effective Learning with A New Benchmark

• keywords: SYSU-30k
• arxiv: https://arxiv.org/abs/1904.03845

Weakly Supervised Tracklet Person Re-Identification by Deep Feature-wise Mutual Learning

https://arxiv.org/abs/1910.14333

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

Viewpoint-Aware Attentive Multi-View Inference for Vehicle Re-Identification

• intro: CVPR 2018
• paper: http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Viewpoint-Aware_Attentive_Multi-View_CVPR_2018_paper.pdf

RAM: A Region-Aware Deep Model for Vehicle Re-Identification

• intro: ICME 2018
• arxiv: https://arxiv.org/abs/1806.09283

Vehicle Re-Identification in Context

• intro: Pattern Recognition - 40th German Conference, (GCPR) 2018, Stuttgart
• project page: https://qmul-vric.github.io/
• arxiv: https://arxiv.org/abs/1809.09409

Vehicle Re-identification Using Quadruple Directional Deep Learning Features

https://arxiv.org/abs/1811.05163

Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification

• intro: ACCV 2018
• arxiv: https://arxiv.org/abs/1812.04239

Vehicle Re-Identification: an Efficient Baseline Using Triplet Embedding

https://arxiv.org/abs/1901.01015

A Two-Stream Siamese Neural Network for Vehicle Re-Identification by Using Non-Overlapping Cameras

• intro: ICIP 2019
• arxiv: https://arxiv.org/abs/1902.01496

CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification

• intro: Accepted for oral presentation at CVPR 2019 with review ratings of 2 strong accepts and 1 accept (work done during an internship at NVIDIA)
• arxiv: https://arxiv.org/abs/1903.09254

Vehicle Re-identification in Aerial Imagery: Dataset and Approach

• intro: Northwestern Polytechnical University
• arxiv: https://arxiv.org/abs/1904.01400

Attributes Guided Feature Learning for Vehicle Re-identification

https://arxiv.org/abs/1905.08997

A unified neural network for object detection, multiple object tracking and vehicle re-identification

https://arxiv.org/abs/1907.03465

Part-Guided Attention Learning for Vehicle Re-Identification

https://arxiv.org/abs/1909.06023

Vehicle Re-identification with Viewpoint-aware Metric Learning

• intro: ICCV 2019
• intro: Beihang University & Tsinghua University & Megvii Technology
• keywords: Viewpoint-Aware Network (VANet)
• arxiv: https://arxiv.org/abs/1910.04104

PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data

• intro: ICCV 2019
• arxiv: https://arxiv.org/abs/2005.00673
• github: https://github.com/NVlabs/PAMTRI

Stripe-based and Attribute-aware Network: A Two-Branch Deep Model for Vehicle Re-identification

https://arxiv.org/abs/1910.05549

Background Segmentation for Vehicle Re-Identification

https://arxiv.org/abs/1910.06613

Vehicle Re-ID Collection

https://github.com/layumi/Vehicle_reID-Collection

awesome-vehicle-re-identification

https://github.com/knwng/awesome-vehicle-re-identification

DCDLearn: Multi-order Deep Cross-distance Learning for Vehicle Re-Identification

https://arxiv.org/abs/2003.11315

Parsing-based View-aware Embedding Network for Vehicle Re-Identification

• intro: CVPR 2020 poster
• arxiv: https://arxiv.org/abs/2004.05021
• github(official): https://github.com/silverbulletmdc/PVEN

Multi-Domain Learning and Identity Mining for Vehicle Re-Identification

• intro: Solution for AI City Challenge, CVPR2020 Workshop
• intro: The 3rd Place Submission to AICity Challenge 2020 Track2
• arxiv: https://arxiv.org/abs/2004.10547
• github: https://github.com/heshuting555/AICITY2020_DMT_VehicleReID

VOC-ReID: Vehicle Re-identification based on Vehicle-Orientation-Camera

• intro: CVPR 2020 workshop, 2nd place solution for AICity2020 Challenge ReID track
• intro: RuiyanAI (睿沿科技)
• arxiv: https://arxiv.org/abs/2004.09164
• github: https://github.com/Xiangyu-CAS/AICity2020-VOC-ReID

VehicleNet: Learning Robust Visual Representation for Vehicle Re-identification

• intro: The 1st Place Submission to AICity Challenge 2020 re-id track (Baidu-UTS submission)
• arxiv: https://arxiv.org/abs/2004.06305
• gtihub: https://github.com/layumi/AICIty-reID-2020
• blog: https://zhuanlan.zhihu.com/p/186905783

Viewpoint-Aware Channel-Wise Attentive Network for Vehicle Re-Identification

• intro: CVPR Workshop 2020
• arxiv: https://arxiv.org/abs/2010.05810

Self-Supervised Visual Attention Learning for Vehicle Re-Identification

https://arxiv.org/abs/2010.09221

AttributeNet: Attribute Enhanced Vehicle Re-Identification

https://arxiv.org/abs/2102.03898

A Strong Baseline for Vehicle Re-Identification

• intro: CVPR Workshop 2021, 5th AI City Challenge
• intro: Cybercore AI
• arxiv: https://arxiv.org/abs/2104.10850
• github: https://github.com/cybercore-co-ltd/track2_aicity_2021

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

FastReID: A Pytorch Toolbox for Real-world Person Re-identification

• intro: SOTA ReID Methods and Toolbox
• intro: JD AI Research
• arxiv: https://arxiv.org/abs/2006.02631
• github: https://github.com/JDAI-CV/fast-reid

light-reid: a toolbox of light reid for fast feature extraction and search

• intro: a toolbox of light-reid learning for faster inference, speed both feature extraction and retrieval stages up to >30x
• github: https://github.com/wangguanan/light-reid

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

ReID_baseline

• intro: Baseline model (with bottleneck) for person ReID (using softmax and triplet loss).
• intro: 一个强力的ReID basemodel
• github: https://github.com/L1aoXingyu/reid_baseline
• blog: https://zhuanlan.zhihu.com/p/40514536

gluon-reid

• intro: A code gallery for person re-identification with mxnet-gluon, and I will reproduce many STOA algorithm.
• github: https://github.com/xiaolai-sqlai/gluon-reid

A PyTorch based strong baseline for person search

https://github.com/DeepAlchemist/deep-person-search

OpenUnReID

• intro: PyTorch open-source toolbox for unsupervised or domain adaptive object re-ID
• github: https://github.com/open-mmlab/OpenUnReID

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

Person Re-Identification - Papers With Code

https://paperswithcode.com/task/person-re-identification

Awesome Person Re-Identification

https://github.com/FDU-VTS/Awesome-Person-Re-Identification