If you have any problems, suggestions or improvements, please submit the issue or PR.
[2021.12.15] Due to my new research interest -- Gigapixel-Level Analysis, I do not have enough time to maintain this repository. I recommend an active repository created by Seokeon.
- Pedestrian Alignment Network
- 2stream Person re-ID
- Pedestrian GAN
- Language Person Search
- DG-Net
- 3D Person re-ID
- [L1aoXingyu] FastReID Baseline
- [michuanhaohao] Bag of Tricks and A Strong Baseline for Deep Person Re-identification
- [layumi] A tiny, friendly, strong pytorch implement of person re-identification baseline
| Dataset | Release time | # identities | # cameras | # images |
|---|---|---|---|---|
| VIPeR | 2007 | 632 | 2 | 1264 |
| ETH1,2,3 | 2007 | 85, 35, 28 | 1 | 8580 |
| QMUL iLIDS | 2009 | 119 | 2 | 476 |
| GRID | 2009 | 1025 | 8 | 1275 |
| CAVIAR4ReID | 2011 | 72 | 2 | 1220 |
| 3DPeS | 2011 | 192 | 8 | 1011 |
| PRID2011 | 2011 | 934 | 2 | 24541 |
| V47 | 2011 | 47 | 2 | 752 |
| WARD | 2012 | 70 | 3 | 4786 |
| SAIVT-Softbio | 2012 | 152 | 8 | 64472 |
| CUHK01 | 2012 | 971 | 2 | 3884 |
| CUHK02 | 2013 | 1816 | 10(5 pairs) | 7264 |
| CUHK03 | 2014 | 1467 | 10(5 pairs) | 13164 |
| RAiD | 2014 | 43 | 4 | 6920 |
| iLIDS-VID | 2014 | 300 | 2 | 42495 |
| MPR Drone | 2014 | 84 | 1 | |
| HDA Person Dataset | 2014 | 53 | 13 | 2976 |
| Shinpuhkan Dataset | 2014 | 24 | 16 | |
| CASIA Gait Database B | 2015 | 124 | 11 | |
| Market1501 | 2015 | 1501 | 6 | 32217 |
| PKU-Reid | 2016 | 114 | 2 | 1824 |
| PRW | 2016 | 932 | 6 | 34,304 |
| CUHK-SYSU | 2016 | 8,432 | - | 18,184 |
| MARS | 2016 | 1261 | 6 | 1,191,003 |
| DukeMTMC-reID (offline) | 2017 | 1812 | 8 | 36441 |
| Airport | 2017 | 9651 | 6 | 39902 |
| MSMT17 | 2018 | 4101 | 15 | 126441 |
| RPIfield | 2018 | 112 | 12 | 601,581 |
| LS-VID | 2019 | 3,772 | 15 | 2,982,685 |
| PersonX | 2019 | 1,266 | 6 | 273,456 |
| COCAS | 2020 | 5,266 | - | 62,382 |
- Person search: New paradigm of person re-identification: A survey and outlook of recent works (IVC2020) [paper]
- Deep Learning for Person Re-identification: A Survey and Outlook (arXiv) [arxiv]
- A Survey of Open-World Person Re-identification (T-CSVT2019) [paper]
- A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets (T-PAMI2018) [paper][github] [arxiv]
- Person Re-identification: Past, Present and Future (arXiv2016) [arxiv]
- A survey of approaches and trends in person re-identification (Image and Vision Computing 2014) [paper]
- Appearance Descriptors for Person Re-identification: a Comprehensive Review (arXiv2013) [arxiv]
- People reidentification in surveillance and forensics: A survey (CSUR2013) [paper]
- Intelligent multi-camera video surveillance: A review (PR Letters2013) [paper]
- Unsupervised Person Re-Identification via Softened Similarity Learning (CVPR2020) [paper]
- Unsupervised Person Re-identification via Multi-label Classification (CVPR2020) [paper]
- Asymetric Co-Teaching for Unsupervised Cross Domain Person Re-Identification (AAAI2020) [arxiv]
- Domain Adaptive Attention Learning for Unsupervised Person Re-Identification (AAAI2020)
- Tracklet Self-Supervised Learning for Unsupervised Person Re-Identification (AAAI2020) [paper]
- [SHRED] Unsupervised Domain Adaptation in Person re-ID via k-Reciprocal Clustering and Large-Scale Heterogeneous Environment Synthesis (WACV2020) [paper]
- [CamStyle] CamStyle: A Novel Data Augmentation Method for Person Re-Identification (TIP2019) [paper][github]
- [DGM+] Dynamic Graph Co-Matching for Unsupervised Video-Based Person Re-Identification (TIP2019) [paper]
- [t-MTL] Tensor Multi-task Learning for Person Re-identification (TIP2019) [paper]
- [UTAL] Unsupervised Tracklet Person Re-Identification (T-PAMI2019) [paper][github]
- [MAR] Unsupervised Person Re-identification by Soft Multilabel Learning (CVPR2019)(Oral) [paper] [arxiv] [github]
- [E2E] Unsupervised Person Image Generation with Semantic Parsing Transformation (CVPR2019)(Oral) [paper] [arxiv] [github]
- [PAUL] Patch-Based Discriminative Feature Learning for Unsupervised Person Re-Identification (CVPR2019) [paper]
- [BUC] A Bottom-Up Clustering Approach to Unsupervised Person Re-identification (AAAI2019) (Oral) [paper] [github]
- Weakly Supervised Person Re-Identification (CVPR2019) [paper] [arxiv]
- Distilled Person Re-identification: Towards a More Scalable System (CVPR2019) [paper]
- [SSG++] Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification (ICCV2019) (Oral) [paper][arxiv]
- [UCDA-CCE] A Novel Unsupervised Camera-Aware Domain Adaptation Framework for Person Re-Identification (ICCV2019) [paper] [arxiv]
- Self-Training With Progressive Augmentation for Unsupervised Cross-Domain Person Re-Identification (ICCV2019) [paper] [arxiv]
- [UGA] Unsupervised Graph Association for Person Re-Identification (ICCV2019) [paper]
- [CFCL] Unsupervised Person Re-Identification by Camera-Aware Similarity Consistency Learning (ICCV2019) [paper]
- [PDA-Net] Cross-Dataset Person Re-Identification via Unsupervised Pose Disentanglement and Adaptation (ICCV2019) [paper] [arxiv]
- Deep Reinforcement Active Learning for Human-in-the-Loop Person Re-Identification (ICCV2019)(Oral) [paper]
- [TJ-AIDL] Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification (CVPR2018) [paper] [arxiv]
- Unsupervised Cross-Dataset Person Re-Identification by Transfer Learning of Spatial-Temporal Patterns (CVPR2018) [paper] [arxiv]
- [DAsy] Domain Adaptation through Synthesis for Unsupervised Person Re-identification (ECCV2018) [paper]
- [RACE] Robust Anchor Embedding for Unsupervised Video Person Re-Identification in the Wild (ECCV2018) [paper]
- [TAUDL] Unsupervised Person Re-identification by Deep Learning Tracklet Association (ECCV2018)(Oral) [paper]
- [CAMEL] Cross-View Asymmetric Metric Learning for Unsupervised Person Re-Identification (ICCV2017) [paper] [arxiv]
- Stepwise Metric Promotion for Unsupervised Video Person Re-Identification (ICCV2017) [paper]
- [UDAP] Unsupervised Domain Adaptive Re-Identification: Theory and Practice (arXiv2018) [paper]
- [ECN] Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification (CVPR2019) [paper]
- [CDs] Clustering and Dynamic Sampling Based Unsupervised Domain Adaptation for Person Re-Identification (ICME2019) [paper]
- [ARN] Adaptation and reidentification network: An unsupervised deep transfer learning approach to person re-identification (CVPR2018) [paper]
- [HHL] Generalizing a person retrieval model hetero-and homogeneously (ECCV2018) [paper]
- [DECAMEL] Unsupervised person re- identification by deep asymmetric metric embedding (PAMI2019) [paper]
- [SPGAN+LMP] Image-image domain adaptation with preserved self-similarity and domain-dissimilarity for person re-identification (CVPR2018) [paper]
- [MMFA] Multi-task mid-level feature alignment network for un- supervised cross-dataset person re-identification (BMVC2018) [paper]
- [CycleGAN] Unpaired image-to- image translation using cycle-consistent adversarial networks (ICCV2017) [paper]
- [PUL] Unsupervised person re-identification: Clustering and fine-tuning (TOMM2018) [paper]
- [PTGAN] Person transfer gan to bridge domain gap for person re-identification (CVPR2018) [paper]
- [proposed] Video-Based Person Re-Identification Using Unsupervised Tracklet Matching (Access2019) [paper]
- [DAL] Deep association learning for unsupervised video person re-identification (BMVC2018) [paper]
- [SMP]* Stepwise metric promotion for unsupervised video person re-identification (ICCV2017) [paper]
- [PAM+LOMO] Multi-shot person re-identification using part appearance mixture (WACV) [paper]
- [DGM+IDE] Dynamic label graph matching for unsupervised video re-identification (ICCV2017) [paper]
- [MDTS] Person re-identification by unsupervised video matching (PR2017) [paper]
- COCAS: A Large-Scale Clothes Changing Person Dataset for Re-Identification (CVPR2020) [paper]
- Online Joint Multi-Metric Adaptation From Frequent Sharing-Subset Mining for Person Re-Identification (CVPR2020) [paper]
- Style Normalization and Restitution for Generalizable Person Re-Identification (CVPR2020) [paper]
- Unsupervised Person Re-Identification via Softened Similarity Learning (CVPR2020) [paper]
- Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking (CVPR2020)(Oral) [paper]
- Inter-Task Association Critic for Cross-Resolution Person Re-Identification (CVPR2020)(Oral) [paper]
- Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification (CVPR2020) [paper]
- Relation-Aware Global Attention for Person Re-identification (CVPR2020) [paper]
- Spatial-Temporal Graph Convolutional Network for Video-based Person Re-identification (CVPR2020) [paper]
- Salience-Guided Cascaded Suppression Network for Person Re-identification (CVPR2020) [paper]
- Bi-directional Interaction Network for Person Search (CVPR2020) [paper]
- Instance Guided Proposal Network for Person Search (CVPR2020)(Oral) [paper]
- AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification (CVPR2020) [paper]
- Unity Style Transfer for Person Re-Identification (CVPR2020) [paper]
- High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification (CVPR2020) [paper]
- Robust Partial Matching for Person Search in the Wild (CVPR2020) [paper]
- Weakly Supervised Discriminative Feature Learning with State Information for Person Identification (CVPR2020) [paper]
- Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification (CVPR2020) [paper]
- Learning Longterm Representations for Person Re-Identification Using Radio Signals (CVPR2020) [paper]
- Camera On-boarding for Person Re-identification using Hypothesis Transfer Learning (CVPR2020) [paper]
- Cross-modality Person re-identification with Shared-Specific Feature Transfer (CVPR2020) [paper]
- Hierarchical Clustering with Hard-batch Triplet Loss for Person Re-identification (CVPR2020) [paper]
- Real-world Person Re-Identification via Degradation Invariance Learning (CVPR2020) [paper]
- Unsupervised Person Re-identification via Multi-label Classification (CVPR2020) [paper]
- Smoothing Adversarial Domain Attack and p-Memory Reconsolidation for Cross-Domain Person Re-Identification (CVPR2020) [paper]
- Norm-Aware Embedding for Efficient Person Search (CVPR2020) [paper]
- TCTS: A Task-Consistent Two-stage Framework for Person Search (CVPR2020) [paper]
- Pose-guided Visible Part Matching for Occluded Person ReID (CVPR2020) [paper]
- Cross-Modal Cross-Domain Moment Alignment Network for Person Search (CVPR2020) [paper]
- Uncertainty-aware Multi-shot Knowledge Distillation for Image-based Object Re-identification (AAAI2020) [arxiv]
- Infrared-Visible Cross-Modal Person Re-Identification with an X Modality (AAAI2020)
- Single Camera Training for Person Re-identification (AAAI2020) [arxiv]
- Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-Identification (AAAI2020) [arxiv]
- Relation-Guided Spatial Attention and Temporal Refinement for Video-based Person Re-Identification (AAAI2020)
- Semantics-Aligned Representation Learning for Person Re-identification (AAAI2020) [arxiv]
- Relation Network for Person Re-identification (AAAI2020) [arxiv]
- Appearance and Motion Enhancement for Video-based Person Re-identification (AAAI2020)
- Rethinking Temporal Fusion for Video-based Person Re-identification on Semantic and Time Aspect (AAAI2020) [arxiv]
- Frame-Guided Region-Aligned Representation for Video Person Re-identification (AAAI2020)
- Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification (AAAI2020)
- Semantic Consistency and Identity Mapping Multi-Component Generative Adversarial Network for Person Re-Identification (WACV2020) [paper]
- [SCR] Learning Discriminative and Generalizable Representations by Spatial-Channel Partition for Person Re-Identification (WACV2020) [paper]
- Video Person Re-Identification using Learned Clip Similarity Aggregation (WACV2020) [paper]
- Pose Guided Gated Fusion for Person Re-identification (WACV2020) [paper]
- Temporal Aggregation with Clip-level Attention for Video-based Person Re-identification (WACV2020) [paper]
- Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification (WACV2020) [paper]
- [REGCT] Robust and Efficient Graph Correspondence Transfer for Person Re-identification (TIP2019) [paper]
- [DHA] Learning Sparse and Identity-preserved Hidden Attributes for Person Re-identification (TIP2019) [paper]
- [RAP] A Richly Annotated Pedestrian Dataset for Person Retrieval in Real Surveillance Scenarios (TIP2019) [paper][github]
- [SCAN] SCAN: Self-and-Collaborative Attention Network for Video Person Re-Identification (TIP2019) [paper][github]
- [FANN] Discriminative Feature Learning With Foreground Attention for Person Re-Identification (TIP2019) [paper]
- Progressive Learning for Person Re-Identification With One Example (TIP2019) [paper][github]
- [PIE] Pose-Invariant Embedding for Deep Person Re-Identification (TIP2019) [paper]
- [UVDL] Uniform and Variational Deep Learning for RGB-D Object Recognition and Person Re-Identification (TIP2019) [paper]
- [CI-CNN] Context-Interactive CNN for Person Re-Identification (TIP2019) [paper]
- [k-KISSME] Kernel Distance Metric Learning Using Pairwise Constraints for Person Re-Identification (TIP2019) [paper][github]
- [MpRL] Multi-Pseudo Regularized Label for Generated Data in Person Re-Identification (TIP2019) [paper][github]
- Deep Representation Learning With Part Loss for Person Re-Identification (TIP2019) [paper]
- [TRL] Video Person Re-Identification by Temporal Residual Learning (TIP2019) [paper]
- [STAL] Spatial-Temporal Attention-Aware Learning for Video-Based Person Re-Identification (TIP2019) [paper]
- [MuDeep] Leader-based Multi-Scale Attention Deep Architecture for Person Re-identification (T-PAMI2019) [paper]
- Learning Part-based Convolutional Features for Person Re-identification (T-PAMI2019) [paper]
- [PGR] Pose-Guided Representation Learning for Person Re-Identification (T-PAMI2019) [paper]
- [HGD] Hierarchical Gaussian Descriptors with Application to Person Re-Identification (T-PAMI2019) [paper]
- A Graph-based Approach for Making Consensus-based Decisions in Image Search and Person Re-identification (T-PAMI2019) [paper]
- [KPM|RW] Person Re-identification with Deep Kronecker-Product Matching and Group-shuffling Random Walk (T-PAMI2019) [paper]
- [MHP] Fine-Grained Multi-human Parsing (IJCV2019) [paper]
- [TPI] Tracking Persons-of-Interest via Unsupervised Representation Adaptation (IJCV2019) [paper]
- [FCDSC] Multi-target Tracking in Multiple Non-overlapping Cameras Using Fast-Constrained Dominant Sets (IJCV2019) [paper]
- [DAN] Learning Discriminative Aggregation Network for Video-Based Face Recognition and Person Re-identification (IJCV2019) [paper]
- Learning Disentangled Representation for Robust Person Re-identification (NeurIPS2019) [paper]
- [AlignedReID++] AlignedReID++: Dynamically matching local information for person re-identification (PR2019) [paper]
- [MSP-CNN] Multi-level Similarity Perception Network for Person Re-identification (TOMM2019) [paper]
- Discriminative Representation Learning for Person Re-identification via Multi-loss Training (JVCIR2019) [paper]
- [DG-Net] Joint Discriminative and Generative Learning for Person Re-identification (CVPR2019)(Oral) [paper] [arxiv]
- [DSA-reID] Densely Semantically Aligned Person Re-Identification (CVPR2019) [paper] [arxiv]
- [DIMN] Generalizable Person Re-identification by Domain-Invariant Mapping Network (CVPR2019) [paper]
- [CASN] Re-Identification with Consistent Attentive Siamese Networks (CVPR2019) [paper] [arxiv]
- Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification (CVPR2019) [paper] [arxiv] [github]
- Re-ranking via Metric Fusion for Object Retrieval and Person Re-identification (CVPR2019) [paper]
- Progressive Pose Attention Transfer for Person Image Generation (CVPR2019)(Oral) [paper] [arxiv] [github]
- Learning to Reduce Dual-level Discrepancy for Infrared-Visible Person Re-identification (CVPR2019) [paper]
- Text Guided Person Image Synthesis (CVPR2019) [paper] [arxiv]
- Learning Context Graph for Person Search (CVPR2019)(Oral) [paper] [arxiv] [github]
- [QEEPS] Query-guided End-to-End Person Search (CVPR2019) [paper] [arxiv] [github]
- Multi-person Articulated Tracking with Spatial and Temporal Embeddings (CVPR2019) [paper] [arxiv]
- Dissecting Person Re-identification from the Viewpoint of Viewpoint (CVPR2019) [paper] [arxiv] [github]
- [CAMA] Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-Identification (CVPR2019) [paper]
- [VRSTC] VRSTC: Occlusion-Free Video Person Re-Identification (CVPR2019) [paper]
- [ATNet] Adaptive Transfer Network for Cross-Domain Person Re-Identification (CVPR2019) [paper]
- [Pyramid] Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training (CVPR2019) [paper] [arxiv]
- [IANet] Interaction-and-Aggregation Network for Person Re-identification (CVPR2019) [paper]
- Skin-based identification from multispectral image data using CNNs (CVPR2019) [paper]
- [VPM] Perceive Where to Focus: Learning Visibility-Aware Part-Level Features for Partial Person Re-Identification (CVPR2019) [paper] [github]
- Attribute-Driven Feature Disentangling and Temporal Aggregation for Video Person Re-Identification (CVPR2019) [paper]
- DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images (CVPR2019) [paper]
- [AANe] AANet: Attribute Attention Network for Person Re-Identifications (CVPR2019) [paper]
- Re-Identification Supervised Texture Generation (CVPR2019) [paper] [arxiv]
- [st-ReID] Spatial-Temporal Person Re-identification (AAAI2019) [arxiv] [github]
- Learning Resolution-Invariant Deep Representations for Person Re-Identification (AAAI2019)(Oral) [paper]
- [HSME] HSME: Hypersphere Manifold Embedding for Visible Thermal Person Re-identification (AAAI2019) [paper]
- [HPM] Horizontal Pyramid Matching for Person Re-identification (AAAI2019) [arxiv]
- [STA] STA: Spatial-Temporal Attention for Large-Scale Video-based Person Re-Identification (AAAI2019) [arxiv]
- Multi-scale 3D Convolution Network for Video Based Person Re-Identification (AAAI2019) [arxiv]
- Backbone Can Not be Trained at Once: Rolling Back to Pre-trained Network for Person Re-Identification (AAAI2019) [arxiv] [github]
- Spatial and Temporal Mutual Promotion for Video-based Person Re-identification (AAAI2019) [arxiv]
- Learning Incremental Triplet Margin for Person Re-identification (AAAI2019) [arxiv]
- [KVM-MN] Learning A Key-Value Memory Co-Attention Matching Network for Person ReIdentification (AAAI2019) [paper]
- [ABD-Net] ABD-Net: Attentive but Diverse Person Re-Identification (ICCV2019) [github] [paper] [arxiv]
- [advPattern] advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns (ICCV2019) [paper] [arxiv]
- Instance-Guided Context Rendering for Cross-Domain Person Re-Identification (ICCV2019) [paper]
- Mixed High-Order Attention Network for Person Re-Identification (ICCV2019) [paper] [arxiv]
- Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification (ICCV2019) [paper] [arxiv]
- Pose-Guided Feature Alignment for Occluded Person Re-Identification (ICCV2019) [paper]
- Robust Person Re-Identification by Modelling Feature Uncertainty (ICCV2019) [paper]
- Co-Segmentation Inspired Attention Networks for Video-Based Person Re-Identification (ICCV2019) [paper]
- RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment (ICCV2019) [paper]
- Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification (ICCV2019) [paper]
- Batch DropBlock Network for Person Re-Identification and Beyond (ICCV2019) [paper] [arxiv]
- Omni-Scale Feature Learning for Person Re-Identification (ICCV2019) [paper] [arxiv]
- Auto-ReID: Searching for a Part-Aware ConvNet for Person Re-Identification (ICCV2019) [paper] [arxiv]
- Second-Order Non-Local Attention Networks for Person Re-Identification (ICCV2019) [paper] [arxiv]
- Global-Local Temporal Representations for Video Person Re-Identification (ICCV2019) [paper] [arxiv] [github]
- Spectral Feature Transformation for Person Re-Identification (ICCV2019) [paper] [arxiv]
- View Confusion Feature Learning for Person Re-Identification (ICCV2019) [paper]
- MVP Matching: A Maximum-Value Perfect Matching for Mining Hard Samples, With Application to Person Re-Identification (ICCV2019) [paper]
- Discriminative Feature Learning With Consistent Attention Regularization for Person Re-Identification (ICCV2019) [paper]
- Foreground-Aware Pyramid Reconstruction for Alignment-Free Occluded Person Re-Identification (ICCV2019) [paper] [arxiv]
- SBSGAN: Suppression of Inter-Domain Background Shift for Person Re-Identification (ICCV2019) [paper] [arxiv]
- Self-Critical Attention Learning for Person Re-Identification (ICCV2019) [paper]
- Temporal Knowledge Propagation for Image-to-Video Person Re-Identification (ICCV2019) [paper] [arxiv]
- Deep Constrained Dominant Sets for Person Re-Identification (ICCV2019) [paper] [arxiv]
- [MGN] Learning Discriminative Features with Multiple Granularities for Person Re-Identification (ACMMM2018) [paper]
- [FD-GAN] FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification (NeurIPS2018) [paper]
- [Multi-pseudo] Multi-pseudo regularized label for generated data in person re-identification (TIP2018) [paper] [arxiv]
- [PAN] Pedestrian Alignment Network for Large-scale Person Re-identification (T-CSVT2018) [paper] [arxiv]
- Person Transfer GAN to Bridge Domain Gap for Person Re-Identification (CVPR2018)(Oral) [paper] [arxiv]
- Disentangled Person Image Generation (CVPR2018)(Oral) [paper] [arxiv]
- Group Consistent Similarity Learning via Deep CRF for Person Re-Identification (CVPR2018)(Oral) [paper]
- Diversity Regularized Spatiotemporal Attention for Video-Based Person Re-Identification (CVPR2018) [paper] [arxiv]
- A Pose-Sensitive Embedding for Person Re-Identification With Expanded Cross Neighborhood Re-Ranking (CVPR2018) [paper] [arxiv]
- Image-Image Domain Adaptation With Preserved Self-Similarity and Domain-Dissimilarity for Person Re-Identification (CVPR2018) [paper] [arxiv]
- Human Semantic Parsing for Person Re-Identification (CVPR2018) [paper] [arxiv]
- Video Person Re-Identification With Competitive Snippet-Similarity Aggregation and Co-Attentive Snippet Embedding (CVPR2018) [paper]
- Mask-Guided Contrastive Attention Model for Person Re-Identification (CVPR2018) [paper]
- Person Re-Identification With Cascaded Pairwise Convolutions (CVPR2018) [paper]
- [MLFN] Multi-Level Factorisation Net for Person Re-Identification (CVPR2018) [paper] [arxiv]
- Attention-Aware Compositional Network for Person Re-Identification (CVPR2018) [paper] [arxiv]
- Deep Group-Shuffling Random Walk for Person Re-Identification (CVPR2018) [paper] [arxiv]
- [HA-CNN] Harmonious Attention Network for Person Re-Identification (CVPR2018) [paper] [arxiv]
- Efficient and Deep Person Re-Identification Using Multi-Level Similarity (CVPR2018) [paper] [arxiv]
- [PT] Pose Transferrable Person Re-Identification (CVPR2018) [paper]
- Adversarially Occluded Samples for Person Re-Identification (CVPR2018) [paper]
- Camera Style Adaptation for Person Re-Identification (CVPR2018) [paper] [arxiv]
- Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning (CVPR2018) [paper]
- Dual Attention Matching Network for Context-Aware Feature Sequence Based Person Re-Identification (CVPR2018) [paper] [arxiv]
- Easy Identification From Better Constraints: Multi-Shot Person Re-Identification From Reference Constraints (CVPR2018) [paper]
- Eliminating Background-Bias for Robust Person Re-Identification (CVPR2018) [paper]
- End-to-End Deep Kronecker-Product Matching for Person Re-Identification (CVPR2018) [paper] [arxiv]
- Exploiting Transitivity for Learning Person Re-Identification Models on a Budget (CVPR2018) [paper]
- Deep Spatial Feature Reconstruction for Partial Person Re-Identification: Alignment-Free Approach (CVPR2018) [paper] [arxiv]
- Resource Aware Person Re-Identification Across Multiple Resolutions (CVPR2018) [paper] [arxiv]
- [DeformGAN] Deformable GANs for Pose-Based Human Image Generation (CVPR2018) [paper] [arxiv]
- Maximum Margin Metric Learning Over Discriminative Nullspace for Person Re-identification (ECCV2018) [paper]
- RCAA: Relational Context-Aware Agents for Person Search (ECCV2018) [paper]
- Generalizing A Person Retrieval Model Hetero- and Homogeneously (ECCV2018) [paper]
- Person Search in Videos with One Portrait Through Visual and Temporal Links (ECCV2018) [paper] [github]
- Person Search by Multi-Scale Matching (ECCV2018) [paper]
- Person Re-identification with Deep Similarity-Guided Graph Neural Network (ECCV2018) [paper]
- [PN-GAN] Pose-Normalized Image Generation for Person Re-identification (ECCV2018) [paper]
- Person Search via A Mask-guided Two-stream CNN Model (ECCV2018) [paper]
- Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association (ECCV2018) [paper]
- Hard-Aware Point-to-Set Deep Metric for Person Re-identification (ECCV2018) [paper]
- Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-Identification (ECCV2018) [paper]
- Adversarial Open-World Person Re-Identification (ECCV2018) [paper]
- [Part-aligned] Part-Aligned Bilinear Representations for Person Re-Identification (ECCV2018) [paper]
- [Mancs] Mancs: A Multi-task Attentional Network with Curriculum Sampling for Person Re-identification (ECCV2018) [paper]
- [PCB] Beyond Part Models: Person Retrieval with Refined Part Pooling (and A Strong Convolutional Baseline) (ECCV2018) [paper]
- [SHaPE] SHaPE: A Novel Graph Theoretic Algorithm for Making Consensus-Based Decisions in Person Re-Identification Systems (ICCV2017) [paper]
- Spatio-Temporal Person Retrieval via Natural Language Queries (ICCV2017) [paper] [arxiv]
- A Two Stream Siamese Convolutional Neural Network for Person Re-Identification (ICCV2017) [paper]
- Efficient Online Local Metric Adaptation via Negative Samples for Person Re-Identification (ICCV2017) [paper]
- Learning View-Invariant Features for Person Identification in Temporally Synchronized Videos Taken by Wearable Cameras (ICCV2017) [paper]
- Deeply-Learned Part-Aligned Representations for Person Re-Identification (ICCV2017) [paper] [arxiv]
- [LSRO] Unlabeled Samples Generated by GAN Improve the Person Re-Identification Baseline in Vitro (ICCV2017)(Spotlight) [paper] [arxiv]
- Pose-Driven Deep Convolutional Model for Person Re-Identification (ICCV2017) [paper] [arxiv]
- Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-Identification (ICCV2017) [paper] [arxiv]
- RGB-Infrared Cross-Modality Person Re-Identification (ICCV2017) [paper]
- Multi-Scale Deep Learning Architectures for Person Re-Identification (ICCV2017) [paper] [arxiv]
- [SVDNet] SVDNet for Pedestrian Retrieval (ICCV2017) [paper] [arxiv]
- [DCF] Learning Deep Context-Aware Features Over Body and Latent Parts for Person Re-Identification (CVPR2017) [paper]
- Beyond Triplet Loss: A Deep Quadruplet Network for Person Re-Identification (CVPR2017) [paper] [arxiv]
- Spindle Net: Person Re-Identification With Human Body Region Guided Feature Decomposition and Fusion (CVPR2017) [paper]
- Re-Ranking Person Re-Identification With k-Reciprocal Encoding (CVPR2017) [paper] [arxiv]
- Person Re-Identification in the Wild (CVPR2017) [paper] [arxiv]
- [SSM] Scalable Person Re-Identification on Supervised Smoothed Manifold (CVPR2017) [paper] [arxiv]
- One-Shot Metric Learning for Person Re-Identification (CVPR2017) [paper]
- Joint Detection and Identification Feature Learning for Person Search (CVPR2017) [paper] [arxiv]
- Multiple People Tracking by Lifted Multicut and Person Re-Identification (CVPR2017) [paper]
- Point to Set Similarity Based Deep Feature Learning for Person Re-Identification (CVPR2017) [paper]
- Fast Person Re-Identification via Cross-Camera Semantic Binary Transformation (CVPR2017) [paper]
- See the Forest for the Trees: Joint Spatial and Temporal Recurrent Neural Networks for Video-Based Person Re-Identification (CVPR2017) [paper]
- Consistent-Aware Deep Learning for Person Re-Identification in a Camera Network (CVPR2017) [paper]
The section is being continually updated. Note that some values have superscript, which indicates their source.
| Year-Conference/Journal | Method | Rank@1 | mAP |
|---|---|---|---|
| 2017--CVPR | DCF | 80.3 | 57.5 |
| 2017--CVPR | SSM | 82.2 | 68.8 |
| 2017--ICCV | SVDNet | 82.3 | 62.1 |
| 2017--ICCV | LSRO | 84.0 | 66.1 |
| 2018--CVPR | DeformGAN | 80.6 | 61.3 |
| 2018--T-CSVT | PAN | 82.8 | 63.4 |
| 2018--TIP | Multi-pseudo | 85.8 | 67.5 |
| 2018--CVPR | PT | 87.7 | 68.9 |
| 2018--ECCV | PN-GAN | 89.4 | 72.6 |
| 2018--CVPR | MLFN | 90.0 | 74.3 |
| 2018--NeurIPS | FD-GAN | 90.5 | 77.7 |
| 2018--CVPR | HA-CNN | 91.2 | 75.7 |
| 2018--ECCV | Part-aligned | 91.7 | 79.6 |
| 2018--ECCV | Mancs | 93.1 | 82.3 |
| 2018--ACMMM | MGN | 95.7 | 86.9 |
| 2019--PR | AlignedReID++ | 91.0 | 77.6 |
| 2019--CVPR | VPM | 93.0 | 80.8 |
| 2019--CVPR | AANet | 93.93 | 83.41 |
| 2019--AAAI | HPM | 94.2 | 82.7 |
| 2019--CVPR | CASN | 94.4 | 82.8 |
| 2019--CVPR | IANet | 94.4 | 83.1 |
| 2019--CVPR | CAMA | 94.7 | 84.5 |
| 2019--CVPR | DG-Net | 94.8 | 86.0 |
| 2019--ICCV | ABD-Net | 95.60 | 88.28 |
| 2019--CVPR | DSA-reID | 95.7 | 87.6 |
| 2019--CVPR | Pyramid | 95.7 | 88.2 |
| 2019--AAAI | st-ReID | 97.2 | 86.7 |
| Year-Conference/Journal | Method | Rank@1 | mAP |
|---|---|---|---|
| 2018--NeurIPS | FD-GAN | 80.0 | 64.5 |
| 2018--ECCV | Mancs | 84.9 | 71.8 |
| 2018--ACMMM | MGN | 88.7 | 78.4 |
| 2019--PR | AlignedReID++ | 80.7 | 68.0 |
| 2019--CVPR | VPM | 83.6 | 72.6 |
| 2019--CVPR | CAMA | 85.8 | 72.9 |
| 2019--CVPR | DSA-reID | 86.2 | 74.3 |
| 2019--AAAI | HPM | 86.6 | 74.3 |
| 2019--CVPR | DG-Net | 86.6 | 74.8 |
| 2019--CVPR | IANet | 87.1 | 73.4 |
| 2019--CVPR | AANet | 87.65 | 74.29 |
| 2019--CVPR | CASN | 87.7 | 73.7 |
| 2019--ICCV | ABD-Net | 89.0 | 78.59 |
| 2019--CVPR | Pyramid | 89.0 | 79.0 |
| 2019--AAAI | st-ReID | 94.0 | 82.8 |
| Year-Conference/Journal | Method | Rank@1 | mAP |
|---|---|---|---|
| 2019--CVPR | IANet | 75.5 | 46.8 |
| 2019--CVPR | DG-Net | 77.2 | 52.3 |
| Year-Conference/Journal | Method | Rank@1 | Rank@5 | Rank@10 | mAP |
|---|---|---|---|---|---|
| 2019--ICCV | UGA | 87.2 | 70.3 | ||
| 2019--ICCV | SSG++ | 86.2 | 94.6 | 96.5 | 68.7 |
| 2018--arXiv | UDAP | 75.8 | 89.5 | 93.2 | 53.7 |
| 2019--ICCV | PDA-Net | 75.2 | 86.3 | 90.2 | 47.6 |
| 2019--CVPR | ECN | 75.1 | 87.6 | 91.6 | 43.0 |
| 2019--ICME | CDs | 71.6 | 81.2 | 84.7 | 39.9 |
| 2018--CVPR | ARN | 70.3 | 80.4 | 86.3 | 39.4 |
| 2019--PAMI | UTAL | 69.2 | 46.2 | ||
| 2019--CVPR | PAUL | 68.5 | 82.4 | 87.4 | 40.1 |
| 2019--CVPR | MAR | 67.7 | 81.9 | 40.0 | |
| 2018--ECCV | DASy | 65.7 | |||
| 2019--ICCV | CFCL | 65.4 | 80.6 | 86.2 | 35.5 |
| 2019--ICCV | UCDA-CCE | 64.3 | 34.5 | ||
| 2018--ECCV | TAUDL | 63.7 | 41.2 | ||
| 2018--ECCV | HHL | 62.2 | 78.8 | 84.0 | 31.4 |
| 2019--AAAI | BUC | 61.9 | 73.5 | 78.2 | 29.6 |
| 2019--PAMI | DECAMEL | 60.2 | 76.0 | 32.4 | |
| 2019--TIP | CamStyle | 58.8 | 78.2 | 84.3 | 31.4 |
| 2018--CVPR | TJ-AIDL | 58.2 | 74.8 | 81.1 | 26.5 |
| 2018--CVPR | SPGAN+LMP | 57.7 | 75.8 | 82.4 | 26.7 |
| 2018--BMVC | MMFA | 56.7 | 75.0 | 81.8 | 27.4 |
| 2017--ICCV | CAMEL | 54.5 | 73.1 | 26.3 | |
| 2018--CVPR | SPGAN | 51.5 | 70.1 | 76.8 | 27.1 |
| Year-Conference/Journal | Method | Rank@1 | Rank@5 | Rank@10 | mAP |
|---|---|---|---|---|---|
| 2019--ICCV | SSG++ | 76.0 | 85.8 | 89.3 | 60.3 |
| 2019--ICCV | UGA | 75.0 | 53.3 | ||
| 2019--CVPR | PAUL | 72.0 | 82.7 | 86.0 | 53.2 |
| 2019--PAMI | UTAL | 69.2 | 46.2 | ||
| 2018--arXiv | UDAP | 68.4 | 80.1 | 83.5 | 49.0 |
| 2019--ICME | CDs | 67.2 | 75.9 | 79.4 | 42.7 |
| 2019--CVPR | MAR | 67.1 | 79.8 | 48.0 | |
| 2019--CVPR | ECN | 63.3 | 75.8 | 80.4 | 40.4 |
| 2019--ICCV | PDA-Net | 63.2 | 77.0 | 82.5 | 45.1 |
| 2018--ECCV | TAUDL | 61.7 | 43.5 | ||
| 2018--CVPR | ARN | 60.2 | 73.9 | 79.5 | 33.4 |
| 2019--ICCV | CFCL | 59.3 | 73.2 | 77.8 | 37.8 |
| 2019--ICCV | UCDA-CCE | 55.4 | 36.7 | ||
| 2019--TIP | CamStyle | 48.4 | 62.5 | 68.9 | 25.1 |
| 2018--ECCV | HHL | 46.9 | 61.0 | 66.7 | 27.2 |
| 2018--CVPR | SPGAN+LMP | 46.4 | 62.3 | 68.0 | 26.2 |
| 2018--BMVC | MMFA | 45.3 | 59.8 | 66.3 | 24.7 |
| 2018--CVPR | TJ-AIDL | 44.3 | 59.6 | 65.0 | 23.0 |
| 2018--CVPR | SPGAN | 41.1 | 56.6 | 63.0 | 22.3 |
| 2019--AAAI | BUC | 40.4 | 52.5 | 58.2 | 22.1 |
| 2017--ICCV | CAMEL | 40.3 | 57.6 | 19.8 | |
| 2017--ICCV | CycleGAN | 38.5 | 19.9 | ||
| 2018--TOMM | PUL | 30.0 | 43.4 | 48.5 | 16.4 |
| 2018--CVPR | PTGAN | 27.4 | 43.6 | 50.7 | 13.5 |
| Year-Conference/Journal | Method | Rank@1 | Rank@5 | Rank@10 | Rank@20 |
|---|---|---|---|---|---|
| 2019--Access | proposed | 91.7 | 96.7 | 98.7 | |
| 2018--BMVC | DAL | 85.3 | 97.0 | 99.6 | |
| 2019--TIP | DGM+ | 81.4 | 95.8 | 98.3 | 99.6 |
| 2017--ICCV | SMP* | 80.9 | 93.3 | 97.8 | 99.4 |
| 2017--ICCV | DGM+MLAPG | 73.1 | 92.5 | 99.0 | |
| 2017--WACV | PAM+LOMO | 70.6 | 90.2 | 97.1 | |
| 2017--ICCV | DGM+IDE | 56.4 | 81.3 | 96.4 | |
| 2019--PAMI | UTAL | 54.7 | 83.1 | 96.2 | |
| 2018--ECCV | RACE | 50.6 | 79.4 | 91.8 | |
| 2018--ECCV | TAUDL | 49.4 | 78.7 | 98.9 | |
| 2018--ECCV | DAsy | 43.0 | |||
| 2017--PR | MDTS | 41.7 | 67.1 | 79.4 | 90.1 |
| Year-Conference/Journal | Method | Rank@1 | Rank@5 | Rank@10 | Rank@20 |
|---|---|---|---|---|---|
| 2019--Access | proposed | 79.1 | 93.5 | 97.5 | |
| 2018--BMVC | DAL | 56.9 | 80.6 | 91.9 | |
| 2018--ECCV | DAsy | 56.5 | |||
| 2017--ICCV | SMP* | 41.7 | 66.3 | 74.1 | 80.7 |
| 2017--ICCV | DGM+MLAPG | 37.1 | 61.3 | 82.0 | |
| 2019--PAMI | UTAL | 35.1 | 59.0 | 83.8 | |
| 2017--WACV | PAM+LOMO | 33.3 | 57.8 | 80.5 | |
| 2017--PR | MDTS | 31.5 | 62.1 | 72.8 | 82.4 |
| 2018--ECCV | TAUDL | 26.7 | 51.3 | 82.0 | |
| 2018--ECCV | RACE | 19.3 | 39.3 | 68.7 |
| Year-Conference/Journal | Method | Rank@1 | Rank@5 | Rank@20 | mAP |
|---|---|---|---|---|---|
| 2019--PAMI | UTAL | 49.9 | 66.4 | 77.8 | 35.2 |
| 2018--BMVC | DAL | 46.8 | 63.9 | 77.5 | 21.4 |
| 2018--ECCV | TAUDL | 43.8 | 59.9 | 72.8 | 29.1 |
| 2018--ECCV | RACE | 43.2 | 57.1 | 67.6 | 24.5 |
| 2019--Access | proposed | 39.7 | 53.2 | 64.1 | 20.1 |
| 2017--ICCV | DGM+MLAPG | 24.6 | 42.6 | 57.2 | 11.8 |
| 2017--ICCV | SMP* | 23.9 | 35.8 | 44.9 | 10.5 |