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 .
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
IVC2020 ) [paper ]arXiv ) [arxiv ]T-CSVT2019 ) [paper ](T-PAMI2018) [paper ][github ] [arxiv ]arXiv2016 ) [arxiv ]Image and Vision Computing 2014 ) [paper ]arXiv2013 ) [arxiv ]CSUR2013 ) [paper ]PR Letters2013 ) [paper ]
(CVPR2020) [paper ](CVPR2020) [paper ](AAAI2020) [arxiv ](AAAI2020) (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 ]CVPR2019 ) [paper ] [arxiv ]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 ]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 ]ICCV2019 )(Oral ) [paper ][TJ-AIDL] Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification (CVPR2018 ) [paper ] [arxiv ]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 ]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 ]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 ]
(CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020)(Oral) [paper ](CVPR2020)(Oral) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020)(Oral) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](CVPR2020) [paper ](AAAI2020) [arxiv ](AAAI2020) (AAAI2020) [arxiv ](AAAI2020) [arxiv ](AAAI2020) (AAAI2020) [arxiv ](AAAI2020) [arxiv ](AAAI2020) (AAAI2020) [arxiv ](AAAI2020) (AAAI2020) (WACV2020) [paper ][SCR] Learning Discriminative and Generalizable Representations by Spatial-Channel Partition for Person Re-Identification (WACV2020) [paper ](WACV2020) [paper ](WACV2020) [paper ](WACV2020) [paper ](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 ](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 ](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 ](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 ](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 ]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 ]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 ]CVPR2019 ) [paper ] [arxiv ] [github ]CVPR2019 ) [paper ]CVPR2019 )(Oral ) [paper ] [arxiv ] [github ]CVPR2019 ) [paper ]CVPR2019 ) [paper ] [arxiv ]CVPR2019 )(Oral ) [paper ] [arxiv ] [github ][QEEPS] Query-guided End-to-End Person Search (CVPR2019 ) [paper ] [arxiv ] [github ]CVPR2019 ) [paper ] [arxiv ]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 ]CVPR2019 ) [paper ][VPM] Perceive Where to Focus: Learning Visibility-Aware Part-Level Features for Partial Person Re-Identification (CVPR2019 ) [paper ] [github ]CVPR2019 ) [paper ]CVPR2019 ) [paper ][AANe] AANet: Attribute Attention Network for Person Re-Identifications (CVPR2019 ) [paper ]CVPR2019 ) [paper ] [arxiv ][st-ReID] Spatial-Temporal Person Re-identification (AAAI2019 ) [arxiv ] [github ]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 ]AAAI2019 ) [arxiv ]AAAI2019 ) [arxiv ] [github ]AAAI2019 ) [arxiv ]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 ]ICCV2019 ) [paper ]ICCV2019 ) [paper ] [arxiv ]ICCV2019 ) [paper ] [arxiv ]ICCV2019 ) [paper ]ICCV2019 ) [paper ]ICCV2019 ) [paper ]ICCV2019 ) [paper ]ICCV2019 ) [paper ]ICCV2019 ) [paper ] [arxiv ]ICCV2019 ) [paper ] [arxiv ]ICCV2019 ) [paper ] [arxiv ]ICCV2019 ) [paper ] [arxiv ]ICCV2019 ) [paper ] [arxiv ] [github ]ICCV2019 ) [paper ] [arxiv ]ICCV2019 ) [paper ]ICCV2019 ) [paper ]ICCV2019 ) [paper ]ICCV2019 ) [paper ] [arxiv ]ICCV2019 ) [paper ] [arxiv ]ICCV2019 ) [paper ]ICCV2019 ) [paper ] [arxiv ]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 ]CVPR2018 )(Oral ) [paper ] [arxiv ]CVPR2018 )(Oral ) [paper ] [arxiv ]CVPR2018 )(Oral ) [paper ]CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ]CVPR2018 ) [paper ]CVPR2018 ) [paper ][MLFN] Multi-Level Factorisation Net for Person Re-Identification (CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ] [arxiv ][HA-CNN] Harmonious Attention Network for Person Re-Identification (CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ] [arxiv ][PT] Pose Transferrable Person Re-Identification (CVPR2018 ) [paper ]CVPR2018 ) [paper ]CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ]CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ]CVPR2018 ) [paper ]CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ]CVPR2018 ) [paper ] [arxiv ]CVPR2018 ) [paper ] [arxiv ][DeformGAN] Deformable GANs for Pose-Based Human Image Generation (CVPR2018 ) [paper ] [arxiv ]ECCV2018 ) [paper ]ECCV2018 ) [paper ]ECCV2018 ) [paper ]ECCV2018 ) [paper ] [github ]ECCV2018 ) [paper ]ECCV2018 ) [paper ][PN-GAN] Pose-Normalized Image Generation for Person Re-identification (ECCV2018 ) [paper ]ECCV2018 ) [paper ]ECCV2018 ) [paper ]ECCV2018 ) [paper ]ECCV2018 ) [paper ]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 ]ICCV2017 ) [paper ] [arxiv ]ICCV2017 ) [paper ]ICCV2017 ) [paper ]ICCV2017 ) [paper ]ICCV2017 ) [paper ] [arxiv ][LSRO] Unlabeled Samples Generated by GAN Improve the Person Re-Identification Baseline in Vitro (ICCV2017 )(Spotlight ) [paper ] [arxiv ]ICCV2017 ) [paper ] [arxiv ]ICCV2017 ) [paper ] [arxiv ]ICCV2017 ) [paper ]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 ]CVPR2017 ) [paper ] [arxiv ]CVPR2017 ) [paper ]CVPR2017 ) [paper ] [arxiv ]CVPR2017 ) [paper ] [arxiv ][SSM] Scalable Person Re-Identification on Supervised Smoothed Manifold (CVPR2017 ) [paper ] [arxiv ]CVPR2017 ) [paper ]CVPR2017 ) [paper ] [arxiv ]CVPR2017 ) [paper ]CVPR2017 ) [paper ]CVPR2017 ) [paper ]CVPR2017 ) [paper ]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
