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Leaderboard

Unsupervised and domain adaptive re-ID methods on public benchmarks. To add some papers not included, you could create an issue or a pull request. Note: the following results are copied from their original papers.

For trained models by OpenUnReID, please refer to MODEL_ZOO.md.

Contents

Unsupervised learning on object re-ID

Market-1501

Method Venue Code mAP(%) R@1(%) R@5(%) R@10(%) Reference
SpCL+ NeurIPS'20 PyTorch (OpenUnReID) 76.0 89.5 96.2 97.5 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
MMT+ ICLR'20 PyTorch (OpenUnReID) 74.3 88.1 96.0 97.5 Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
SpCL NeurIPS'20 PyTorch 73.1 88.1 95.1 97.0 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
Strong Baseline N/A PyTorch (OpenUnReID) 70.5 87.9 95.7 97.1 N/A
HCT CVPR'20 Empty 56.4 80.0 91.6 95.2 Hierarchical Clustering with Hard-batch Triplet Loss for Person Re-identification
MMCL CVPR'20 PyTorch 45.5 80.3 89.4 92.3 Unsupervised Person Re-Identification via Multi-Label Classification
SSL CVPR'20 PyTorch (Unofficial) 37.8 71.7 83.8 87.4 Unsupervised Person Re-identification via Softened Similarity Learning
BUC AAAI'19 PyTorch 38.3 66.2 79.6 84.5 A Bottom-up Clustering Approach to Unsupervised Person Re-identification

DukeMTMC-reID

Method Venue Code mAP(%) R@1(%) R@5(%) R@10(%) Reference
SpCL+ NeurIPS'20 PyTorch (OpenUnReID) 67.1 82.4 90.8 93.0 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
MMT+ ICLR'20 PyTorch (OpenUnReID) 60.3 75.6 86.0 89.2 Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
SpCL NeurIPS'20 PyTorch 65.3 81.2 90.3 92.2 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
Strong Baseline N/A PyTorch (OpenUnReID) 54.7 72.9 83.5 87.2 N/A
HCT CVPR'20 Empty 50.7 69.6 83.4 87.4 Hierarchical Clustering with Hard-batch Triplet Loss for Person Re-identification
MMCL CVPR'20 PyTorch 40.2 65.2 75.9 80.0 Unsupervised Person Re-Identification via Multi-Label Classification
SSL CVPR'20 PyTorch (Unofficial) 28.6 52.5 63.5 68.9 Unsupervised Person Re-identification via Softened Similarity Learning
BUC AAAI'19 PyTorch 27.5 47.4 62.6 68.4 A Bottom-up Clustering Approach to Unsupervised Person Re-identification

MSMT17

Method Venue Code mAP(%) R@1(%) R@5(%) R@10(%) Reference
SpCL NeurIPS'20 PyTorch 19.1 42.3 55.6 61.2 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
MMCL CVPR'20 PyTorch 11.2 35.4 44.8 49.8 Unsupervised Person Re-Identification via Multi-Label Classification

Unsupervised domain adaptation on object re-ID

Market-1501 -> DukeMTMC-reID

Method Venue Code mAP(%) R@1(%) R@5(%) R@10(%) Reference
SpCL+ NeurIPS'20 PyTorch (OpenUnReID) 70.4 83.8 91.2 93.4 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
MMT+ ICLR'20 PyTorch (OpenUnReID) 67.7 80.3 89.9 92.9 Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
SpCL NeurIPS'20 PyTorch 68.8 82.9 90.1 92.5 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
MEB-Net ECCV'20 PyTorch 66.1 79.6 88.3 92.2 Multiple Expert Brainstorming for Domain Adaptive Person Re-identification
MMT ICLR'20 PyTorch 65.1 78.0 88.8 92.5 Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
Strong Baseline N/A PyTorch (OpenUnReID) 60.4 75.9 86.2 89.8 N/A
AD-Cluster CVPR'20 PyTorch 54.1 72.6 82.5 85.5 AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification
SNR CVPR'20 - 58.1 76.3 - - Style Normalization and Restitution for Generalizable Person Re-identification
MMCL CVPR'20 PyTorch 51.4 72.4 82.9 85.0 Unsupervised Person Re-Identification via Multi-Label Classification
ECN++ TPAMI'20 - 54.4 74.0 83.7 87.4 Learning to Adapt Invariance in Memory for Person Re-identification
UDA_TP PR'20 PyTorch or OpenUnReID 49.0 68.4 80.1 83.5 Unsupervised Domain Adaptive Re-Identification: Theory and Practice
SSG ICCV'19 PyTorch 53.4 73.0 80.6 83.2 Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification
PCB-PAST ICCV'19 PyTorch 54.3 72.4 - - Self-Training With Progressive Augmentation for Unsupervised Cross-Domain Person Re-Identification
CR-GAN ICCV'19 - 48.6 68.9 80.2 84.7 Instance-Guided Context Rendering for Cross-Domain Person Re-Identification
PDA-Net ICCV'19 - 45.1 63.2 77.0 82.5 Cross-Dataset Person Re-Identification via Unsupervised Pose Disentanglement and Adaptation
UCDA ICCV'19 - 31.0 47.7 - - A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification
ECN CVPR'19 PyTorch 40.4 63.3 75.8 80.4 Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification
HHL ECCV'18 PyTorch 33.4 60.2 73.9 79.5 Generalizing A Person Retrieval Model Hetero- and Homogeneously
SPGAN CVPR'18 PyTorch or OpenUnReID 22.3 41.1 56.6 63.0 Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification
TJ-AIDL CVPR'18 - 23.0 44.3 59.6 65.0 Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification
PUL TOMM'18 PyTorch 16.4 30.0 43.4 48.5 Unsupervised Person Re-identification: Clustering and Fine-tuning

DukeMTMC-reID -> Market-1501

Method Venue Code mAP(%) R@1(%) R@5(%) R@10(%) Reference
SpCL+ NeurIPS'20 PyTorch (OpenUnReID) 78.2 90.5 96.6 97.8 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
MMT+ ICLR'20 PyTorch (OpenUnReID) 80.9 92.2 97.6 98.4 Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
SpCL NeurIPS'20 PyTorch 76.7 90.3 96.2 97.7 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
MEB-Net ECCV'20 PyTorch 76.0 89.9 96.0 97.5 Multiple Expert Brainstorming for Domain Adaptive Person Re-identification
Strong Baseline N/A PyTorch (OpenUnReID) 75.6 90.9 96.6 97.8 N/A
MMT ICLR'20 PyTorch 71.2 87.7 94.9 96.9 Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
AD-Cluster CVPR'20 PyTorch 68.3 86.7 94.4 96.5 AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification
SNR CVPR'20 - 61.7 82.8 - - Style Normalization and Restitution for Generalizable Person Re-identification
MMCL CVPR'20 PyTorch 60.4 84.4 92.8 95.0 Unsupervised Person Re-Identification via Multi-Label Classification
ECN++ TPAMI'20 - 63.8 84.1 92.8 95.4 Learning to Adapt Invariance in Memory for Person Re-identification
UDA_TP PR'20 PyTorch or OpenUnReID 53.7 75.8 89.5 93.2 Unsupervised Domain Adaptive Re-Identification: Theory and Practice
SSG ICCV'19 PyTorch 58.3 80.0 90.0 92.4 Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification
PCB-PAST ICCV'19 PyTorch 54.6 78.4 - - Self-Training With Progressive Augmentation for Unsupervised Cross-Domain Person Re-Identification
CR-GAN ICCV'19 - 54.0 77.7 89.7 92.7 Instance-Guided Context Rendering for Cross-Domain Person Re-Identification
PDA-Net ICCV'19 - 47.6 75.2 86.3 90.2 Cross-Dataset Person Re-Identification via Unsupervised Pose Disentanglement and Adaptation
UCDA ICCV'19 - 30.9 60.4 - - A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification
ECN CVPR'19 PyTorch 43.0 75.1 87.6 91.6 Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification
HHL ECCV'18 PyTorch 31.4 62.2 78.8 84.05 Generalizing A Person Retrieval Model Hetero- and Homogeneously
SPGAN CVPR'18 PyTorch or OpenUnReID 22.8 51.5 70.1 76.8 Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification
TJ-AIDL CVPR'18 - 26.5 58.2 74.8 81.1 Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification
PUL TOMM'18 PyTorch 20.5 45.5 60.7 66.7 Unsupervised Person Re-identification: Clustering and Fine-tuning

Market-1501 -> MSMT17

Method Venue Code mAP(%) R@1(%) R@5(%) R@10(%) Reference
SpCL NeurIPS'20 PyTorch 26.8 53.7 65.0 69.8 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
MMT ICLR'20 PyTorch 22.9 49.2 63.1 68.8 Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
MMCL CVPR'20 PyTorch 15.1 40.8 51.8 56.7 Unsupervised Person Re-Identification via Multi-Label Classification
ECN++ TPAMI'20 - 15.2 40.4 53.1 58.7 Learning to Adapt Invariance in Memory for Person Re-identification
SSG ICCV'19 PyTorch 13.2 31.6 - 49.6 Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification
ECN CVPR'19 PyTorch 8.5 25.3 36.3 42.1 Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification
PTGAN CVPR'18 - 2.9 10.2 - 24.4 Person Transfer GAN to Bridge Domain Gap for Person Re-Identification

DukeMTMC-reID -> MSMT17

Method Venue Code mAP(%) R@1(%) R@5(%) R@10(%) Reference
SpCL NeurIPS'20 PyTorch 26.5 53.1 65.8 70.5 Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID
MMT ICLR'20 PyTorch 23.3 50.1 63.9 69.8 Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification
MMCL CVPR'20 PyTorch 16.2 43.6 54.3 58.9 Unsupervised Person Re-Identification via Multi-Label Classification
ECN++ TPAMI'20 - 16.0 42.5 55.9 61.5 Learning to Adapt Invariance in Memory for Person Re-identification
SSG ICCV'19 PyTorch 13.3 32.2 - 51.2 Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification
ECN CVPR'19 PyTorch 10.2 30.2 41.5 46.8 Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification
PTGAN CVPR'18 - 3.3 11.8 - 27.4 Person Transfer GAN to Bridge Domain Gap for Person Re-Identification