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Earlier:
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And:
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Cameras
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1510
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Zhu, X.K.[Xiao-Ke],
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Videos, Cameras, Dictionaries, Feature extraction, Training,
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IP(26), No. 5, May 2017, pp. 2438-2453.
IEEE DOI
1704
BibRef
Earlier: A2, A1, A3, A5, A5, A6, Only:
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ICCV15(3200-3208)
IEEE DOI
1602
Cameras
BibRef
Zheng, L.[Liang],
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Tian, L.[Lu],
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ICCV15(1116-1124)
IEEE DOI
1602
Benchmark testing
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Zhao, R.[Rui],
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PAMI(39), No. 2, February 2017, pp. 356-370.
IEEE DOI
1702
BibRef
Earlier:
Learning Mid-level Filters for Person Re-identification,
CVPR14(144-151)
IEEE DOI
1409
BibRef
Earlier:
Person Re-identification by Salience Matching,
ICCV13(2528-2535)
IEEE DOI
1403
BibRef
Earlier:
Unsupervised Salience Learning for Person Re-identification,
CVPR13(3586-3593)
IEEE DOI
1309
Mid-level filter; person re-identification.
Salience matching; person re-identification; recognition
BibRef
Chen, D.P.[Da-Peng],
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Exemplar-Guided Similarity Learning on Polynomial Kernel Feature Map
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IJCV(123), No. 3, July 2017, pp. 392-414.
Springer DOI
1706
BibRef
Earlier: A1, A2, A4, A6, Only:
Similarity Learning with Spatial Constraints for Person
Re-identification,
CVPR16(1268-1277)
IEEE DOI
1612
BibRef
Earlier: A1, A2, A5, A6, A3, Only:
Similarity learning on an explicit polynomial kernel feature map for
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CVPR15(1565-1573)
IEEE DOI
1510
BibRef
Chen, G.,
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Feng, J.J.[Jian-Jiang],
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Localized multi-kernel discriminative canonical correlation analysis
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ICIP17(111-115)
IEEE DOI
1803
Cameras, Correlation, Kernel, Manifolds, Measurement, Optimization,
Videos, Person re-identification, canonical correlation analysis,
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Dong, H.S.[Hu-Sheng],
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DOI Link
1709
BibRef
An, L.,
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IEEE DOI
1808
Cameras, Measurement, Feature extraction, Image color analysis,
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group sparse representation
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Karanam, S.,
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Learning Affine Hull Representations for Multi-Shot Person
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CirSysVideo(28), No. 10, October 2018, pp. 2500-2512.
IEEE DOI
1811
Measurement, Cameras, Learning systems, Image sequences, Probes,
Image recognition, Approximation algorithms, Re-identification,
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BibRef
Wang, H.X.[Han-Xiao],
Zhu, X.T.[Xia-Tian],
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Person Re-identification in Identity Regression Space,
IJCV(126), No. 12, December 2018, pp. 1288-1310.
Springer DOI
1811
BibRef
Li, W.[Wei],
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Elsevier DOI
2103
Person search, Person re-identification, Person detection,
Knowledge distillation, Scalability, Model inference efficiency
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Li, M.X.[Min-Xian],
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Gong, S.G.[Shao-Gang],
Unsupervised Person Re-identification by Deep Learning Tracklet
Association,
ECCV18(II: 772-788).
Springer DOI
1810
BibRef
Dai, J.,
Zhang, P.,
Wang, D.,
Lu, H.,
Wang, H.,
Video Person Re-Identification by Temporal Residual Learning,
IP(28), No. 3, March 2019, pp. 1366-1377.
IEEE DOI
1812
Feature extraction, Video sequences, Cameras, Face recognition,
Image recognition, Data mining, Bidirectional control,
temporal residual learning
BibRef
Huang, Y.[Yan],
Xu, J.S.[Jing-Song],
Wu, Q.A.[Qi-Ang],
Zheng, Z.D.[Zhe-Dong],
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Zhang, J.[Jian],
Multi-Pseudo Regularized Label for Generated Data in Person
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IP(28), No. 3, March 2019, pp. 1391-1403.
IEEE DOI
1812
Training, Semisupervised learning, Training data,
Data models, Machine learning, Task analysis,
semi-supervised learning
BibRef
Huang, L.Q.[Li-Qin],
Yang, Q.Q.[Qing-Qing],
Wu, J.Y.[Jun-Yi],
Huang, Y.[Yan],
Wu, Q.A.[Qi-Ang],
Xu, J.S.[Jing-Song],
Generated Data With Sparse Regularized Multi-Pseudo Label for Person
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SPLetters(27), 2020, pp. 391-395.
IEEE DOI
2004
Person re-identification, generated data, sparse pseudo label
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Xian, Y.Q.[Yu-Qiao],
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Enhanced multi-dataset transfer learning method for unsupervised person
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IET-CV(12), No. 8, December 2018, pp. 1219-1227.
DOI Link
1812
BibRef
Lian, S.C.[Si-Cheng],
Jiang, W.T.[Wei-Tao],
Hu, H.F.[Hai-Feng],
Attention-Aligned Network for Person Re-Identification,
CirSysVideo(31), No. 8, August 2021, pp. 3140-3153.
IEEE DOI
2108
Active appearance model, Feature extraction, Visualization,
Learning systems, Clutter, Training, Measurement,
omnibearing foreground-aware attention
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Subramanyam, A.V.,
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Ahuja, R.,
Robust Discriminative Subspace Learning for Person Reidentification,
SPLetters(26), No. 1, January 2019, pp. 154-158.
IEEE DOI
1901
covariance analysis, iterative methods,
learning (artificial intelligence), video surveillance,
person Re-identification
BibRef
Xu, X.Y.[Xiao-Yue],
Chen, Y.[Ying],
Video-based person re-identification based on regularised hull distance
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IET-CV(13), No. 4, June 2019, pp. 385-394.
DOI Link
1906
BibRef
Li, W.H.[Wei-Hong],
Zhong, Z.[Zhuowei],
Zheng, W.S.[Wei-Shi],
One-pass person re-identification by sketch online discriminant
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PR(93), 2019, pp. 237-250.
Elsevier DOI
1906
Online learning, Person re-identification, Discriminant feature extraction
BibRef
Zhong, W.L.[Wei-Lin],
Zhang, T.[Tao],
Jiang, L.F.[Lin-Feng],
Ji, J.S.[Jin-Sheng],
Zhang, Z.H.[Zeng-Hui],
Xiong, H.L.[Hui-Lin],
Discriminative representation learning for person re-identification
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JVCIR(62), 2019, pp. 267-278.
Elsevier DOI
1908
Person re-identification, Multi-loss training, Inter-center loss
BibRef
Yang, H.[Hua],
Cheng, Z.X.[Zhao-Xi],
Chen, L.[Lin],
Reranking optimization for person re-identification under
temporal-spatial information and common network consistency
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PRL(127), 2019, pp. 146-155.
Elsevier DOI
1911
Temporal-spatial constraints, Network consistence constraints,
Person reidentification, Topology information, Global optimization
BibRef
Chen, L.[Lin],
Yang, H.[Hua],
Gao, Z.Y.[Zhi-Yong],
Comprehensive feature fusion mechanism for video-based person
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SP:IC(84), 2020, pp. 115835.
Elsevier DOI
2004
Person re-identification, Attention, Residual learning, Feature fusion
BibRef
Yan, Y.C.[Yi-Chao],
Ni, B.B.[Bing-Bing],
Liu, J.X.[Jin-Xian],
Yang, X.K.[Xiao-Kang],
Multi-level attention model for person re-identification,
PRL(127), 2019, pp. 156-164.
Elsevier DOI
1911
BibRef
Zheng, A.,
Zhang, X.,
Jiang, B.,
Luo, B.,
Li, C.,
A Subspace Learning Approach to Multishot Person Reidentification,
SMCS(50), No. 1, January 2020, pp. 149-158.
IEEE DOI
2001
Cameras, Sparse matrices, Image color analysis, Robustness,
Image sequences, Surveillance, subspace learning
BibRef
Choi, H.[Hyunguk],
Yow, K.C.[Kin Choong],
Jeon, M.[Moongu],
Training approach using the shallow model and hard triplet mining for
person re-identification,
IET-IPR(14), No. 2, February 2020, pp. 256-266.
DOI Link
2001
BibRef
Zhang, Y.F.[Yi-Fu],
Wang, C.Y.[Chun-Yu],
Wang, X.G.[Xing-Gang],
Zeng, W.J.[Wen-Jun],
Liu, W.Y.[Wen-Yu],
FairMOT: On the Fairness of Detection and Re-identification in Multiple
Object Tracking,
IJCV(129), No. 11, November 2021, pp. 3069-3087.
Springer DOI
2110
BibRef
Wang, C.[Cheng],
Zhang, Q.[Qian],
Huang, C.[Chang],
Liu, W.Y.[Wen-Yu],
Wang, X.G.[Xing-Gang],
Mancs: A Multi-task Attentional Network with Curriculum Sampling for
Person Re-Identification,
ECCV18(II: 384-400).
Springer DOI
1810
BibRef
Lin, Y.T.[Yu-Tian],
Wu, Y.[Yu],
Yan, C.G.[Cheng-Gang],
Xu, M.L.[Ming-Liang],
Yang, Y.[Yi],
Unsupervised Person Re-identification via Cross-Camera Similarity
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IP(29), 2020, pp. 5481-5490.
IEEE DOI
2005
BibRef
Zhu, B.[Bin],
Xu, T.K.[Tong-Kun],
Zheng, B.[Bolun],
Zhang, Q.[Quan],
Sun, Y.Q.[Yao-Qi],
Liu, A.[Anan],
Mao, Z.D.[Zhen-Dong],
Yan, C.G.[Cheng-Gang],
Evolution of ICTs-empowered-identification:
A general re-ranking method for person re-identification,
PRL(150), 2021, pp. 94-100.
Elsevier DOI
2109
Person re-identification, Re-ranking, Feature relation map
BibRef
Lin, Y.T.[Yu-Tian],
Xie, L.X.[Ling-Xi],
Wu, Y.[Yu],
Yan, C.G.[Cheng-Gang],
Tian, Q.[Qi],
Unsupervised Person Re-Identification via Softened Similarity
Learning,
CVPR20(3387-3396)
IEEE DOI
2008
Cameras, Training, Quantization (signal), Feature extraction,
Task analysis, Robustness, Machine learning
BibRef
Li, Y.,
Lin, C.,
Lin, Y.,
Wang, Y.F.,
Cross-Dataset Person Re-Identification via Unsupervised Pose
Disentanglement and Adaptation,
ICCV19(7918-7928)
IEEE DOI
2004
feature extraction, image representation,
learning (artificial intelligence), pose estimation, Training
BibRef
Jiang, M.[Min],
Li, C.[Cong],
Kong, J.[Jun],
Teng, Z.D.[Zhen-De],
Zhuang, D.F.[Dan-Feng],
Cross-level reinforced attention network for person re-identification,
JVCIR(69), 2020, pp. 102775.
Elsevier DOI
2006
Person re-identification, Features of different levels,
Soft attention, Hard attention, Reinforced attention
BibRef
Ning, M.[Munan],
Zeng, K.[Kaiwei],
Guo, Y.[Yang],
Wang, Y.[Yaohua],
Deviation based clustering for unsupervised person re-identification,
PRL(135), 2020, pp. 237-243.
Elsevier DOI
2006
Person re-identification, Neural networks, Clustering, Unsupervised learning
BibRef
Zhou, Q.Q.[Qin-Qin],
Zhong, B.N.[Bi-Neng],
Lan, X.Y.[Xiang-Yuan],
Sun, G.[Gan],
Zhang, Y.L.[Yu-Lun],
Zhang, B.C.[Bao-Chang],
Ji, R.R.[Rong-Rong],
Fine-Grained Spatial Alignment Model for Person Re-Identification
With Focal Triplet Loss,
IP(29), 2020, pp. 7578-7589.
IEEE DOI
2007
Person re-identification, spatial alignment, focal triplet loss
BibRef
Zheng, F.[Feng],
Deng, C.[Cheng],
Sun, X.[Xing],
Jiang, X.Y.[Xin-Yang],
Guo, X.W.[Xiao-Wei],
Yu, Z.Q.[Zong-Qiao],
Huang, F.Y.[Fei-Yue],
Ji, R.R.[Rong-Rong],
Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training,
CVPR19(8506-8514).
IEEE DOI
2002
BibRef
Huang, H.J.[Hou-Jing],
Yang, W.J.[Wen-Jie],
Lin, J.B.[Jin-Bin],
Huang, G.[Guan],
Xu, J.M.[Jia-Miao],
Wang, G.L.[Guo-Li],
Chen, X.T.[Xiao-Tang],
Huang, K.Q.[Kai-Qi],
Improve Person Re-Identification With Part Awareness Learning,
IP(29), 2020, pp. 7468-7481.
IEEE DOI
2007
Person re-identification, part awareness, part segmentation, multi-task learning
BibRef
Yang, F.X.[Feng-Xiang],
Zhong, Z.[Zhun],
Luo, Z.M.[Zhi-Ming],
Lian, S.[Sheng],
Li, S.Z.[Shao-Zi],
Leveraging Virtual and Real Person for Unsupervised Person
Re-Identification,
MultMed(22), No. 9, September 2020, pp. 2444-2453.
IEEE DOI
2008
Training, Cameras, Data mining, Training data, Feature extraction,
Annotations, Person re-identification, collaborative filtering
BibRef
Li, S.[Shuai],
Song, W.F.[Wen-Feng],
Fang, Z.[Zheng],
Shi, J.Y.[Jia-Ying],
Hao, A.M.[Ai-Min],
Zhao, Q.P.[Qin-Ping],
Qin, H.[Hong],
Long-Short Temporal-Spatial Clues Excited Network for Robust Person
Re-identification,
IJCV(128), No. 12, December 2020, pp. 2936-2961.
Springer DOI
2010
BibRef
And:
Correction:
IJCV(129), No. 9, September 2021, pp. 2730-2730.
Springer DOI
2108
BibRef
Han, C.,
Zheng, R.,
Gao, C.,
Sang, N.,
Complementation-Reinforced Attention Network for Person
Re-Identification,
CirSysVideo(30), No. 10, October 2020, pp. 3433-3445.
IEEE DOI
2010
Task analysis, Redundancy, Feature extraction, Head, Visualization,
Optimization, Measurement, Person re-identification, attention, complementation
BibRef
Luo, J.,
Liu, Y.,
Gao, C.,
Sang, N.,
Learning What and Where from Attributes to Improve Person
Re-Identification,
ICIP19(165-169)
IEEE DOI
1910
Person re-identification, attribute, fusion, feature attention
BibRef
Chen, K.,
Chen, Y.,
Han, C.,
Sang, N.,
Gao, C.,
Wang, R.,
Improving Person Re-Identification by Adaptive Hard Sample Mining,
ICIP18(1638-1642)
IEEE DOI
1809
Training, Adaptation models, Computational modeling,
Machine learning, Robustness, Cameras, Task analysis,
Deep Learning
BibRef
Liu, X.K.[Xiao-Kai],
Bi, S.[Sheng],
Fang, S.J.[Shao-Jun],
Bouridane, A.[Ahmed],
Bayesian Inferred Self-Attentive Aggregation for Multi-Shot Person
Re-Identification,
CirSysVideo(30), No. 10, October 2020, pp. 3446-3458.
IEEE DOI
2010
Neural networks, Semantics, Feature extraction, Bayes methods,
Robustness, Cameras, Machine learning,
collective aggregation
BibRef
Li, H.F.[Hua-Feng],
Yan, S.L.[Shuang-Lin],
Yu, Z.T.[Zheng-Tao],
Tao, D.P.[Da-Peng],
Attribute-Identity Embedding and Self-Supervised Learning for
Scalable Person Re-Identification,
CirSysVideo(30), No. 10, October 2020, pp. 3472-3485.
IEEE DOI
2010
Visualization, Semantics, Dictionaries, Training, Machine learning,
Predictive models, Adaptation models, Person re-identification,
attribute space
BibRef
Liu, M.,
Qu, L.,
Nie, L.,
Liu, M.,
Duan, L.,
Chen, B.,
Iterative Local-Global Collaboration Learning Towards One-Shot Video
Person Re-Identification,
IP(29), 2020, pp. 9360-9372.
IEEE DOI
2010
One-shot learning, video person re-identification,
variational information bottleneck,
dynamic sample selection
BibRef
Li, S.S.[Si-Shang],
Liu, X.L.[Xue-Liang],
Zhao, Y.[Ye],
Wang, M.[Meng],
Person re-identification based on multi-scale constraint network,
PRL(138), 2020, pp. 403-409.
Elsevier DOI
1806
Multi-scale, Person Re-ID, TriHard loss
BibRef
Fu, D.,
Xin, B.,
Wang, J.,
Chen, D.,
Bao, J.,
Hua, G.,
Li, H.,
Improving Person Re-Identification With Iterative Impression
Aggregation,
IP(29), 2020, pp. 9559-9571.
IEEE DOI
2011
Measurement, Computational modeling, Standards, Benchmark testing,
Task analysis, Analytical models, Training,
post-processing
BibRef
Zhao, Y.[Yu],
Shu, Q.Y.[Qiao-Yuan],
Fu, K.[Keren],
Wei, P.C.[Peng-Cheng],
Zhan, J.[Jian],
Joint patch and instance discrimination learning for unsupervised
person re-identification,
IVC(103), 2020, pp. 104000.
Elsevier DOI
2011
Unsupervised person re-identification,
Large-scale person re-ID, Instance-wise supervision, Joint training
BibRef
Geng, Y.B.[Yan-Bing],
Lian, Y.J.[Yong-Jian],
Zhou, M.L.[Ming-Liang],
Kong, Y.X.[Yi-Xue],
Zhu, Y.N.[Yi-Nong],
Exploiting multigranular salient features with hierarchical
multi-mode attention network for pedestrian re-IDentification,
JVCIR(73), 2020, pp. 102914.
Elsevier DOI
2012
Pedestrian re-identification, Hierarchical,
Multi-mode attention network, Hierarchical adaptive fusion, Fused attention
BibRef
Liu, T.,
Luo, W.,
Ma, L.,
Huang, J.J.,
Stathaki, T.,
Dai, T.,
Coupled Network for Robust Pedestrian Detection With Gated
Multi-Layer Feature Extraction and Deformable Occlusion Handling,
IP(30), 2021, pp. 754-766.
IEEE DOI
2012
Feature extraction, Logic gates, Proposals, Detectors, Task analysis,
Neural networks, Forestry, Pedestrian detection, coupled network,
deformable RoI-pooling
BibRef
Huang, Y.[Yewen],
Huang, Y.[Yi],
Hu, H.F.[Hai-Feng],
Chen, D.[Dihu],
Su, T.[Tao],
Deeply Associative Two-Stage Representations Learning Based on Labels
Interval Extension Loss and Group Loss for Person Re-Identification,
CirSysVideo(30), No. 12, December 2020, pp. 4526-4539.
IEEE DOI
2012
Feature extraction, Pose estimation, Training, Semantics,
Task analysis, Cameras, video surveillance
BibRef
Yu, Y.B.[Yang-Bin],
Zeng, Y.[Ying],
Hu, H.F.[Hai-Feng],
Chen, D.[Dihu],
Two-Branch Asymmetric Model With Alternately Clustering for
Unsupervised Person Re-Identification,
SPLetters(29), 2022, pp. 75-79.
IEEE DOI
2202
Training, Residual neural networks, Person Re-identification,
unsupervised person Re-identification, contrastive learning
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Huang, Y.[Yewen],
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2105
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Adaptively Leverage Unlabeled Tracklets Based on Part Attention Model
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IEEE DOI
2012
Training, Adaptation models, Data models, Reliability, Estimation,
Noise measurement, Probes, Person re-ID, few-example, noisy labels
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IP(30), 2021, pp. 1623-1638.
IEEE DOI
2101
Visualization, Semantics, Training, Pattern matching,
Context modeling, Measurement, Cameras,
correspondence template ensemble
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Liu, Y.,
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IP(30), 2021, pp. 2060-2071.
IEEE DOI
2101
Feature extraction, Cameras, Data models, Body regions, Training,
Visualization, Spatiotemporal phenomena, attention
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Liu, M.,
Raychaudhuri, D.S.,
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Learning Person Re-Identification Models From Videos With Weak
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IP(30), 2021, pp. 3017-3028.
IEEE DOI
2102
Videos, Annotations, Labeling, Task analysis, Feature extraction,
Training, Reliability, Video person re-identification,
co-person attention mechanism
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IVC(106), 2021, pp. 104068.
Elsevier DOI
2102
Person re-identification, Graph neural network,
Intra and inter frame, Body part, Video matching
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Liu, H.J.[Hai-Jun],
Chai, Y.X.[Yan-Xia],
Tan, X.O.[Xia-Oheng],
Li, D.[Dong],
Zhou, X.C.[Xi-Chuan],
Strong but Simple Baseline With Dual-Granularity Triplet Loss for
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SPLetters(28), 2021, pp. 653-657.
IEEE DOI
2104
Training, Measurement, Testing,
Organizations, Neck, Focusing, Dual-granularity triplet loss,
visible-thermal person re-identification
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Huang, Y.[Yan],
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Xu, J.S.[Jing-Song],
Zhong, Y.[Yi],
Zhang, Z.X.[Zhao-Xiang],
Unsupervised Domain Adaptation with Background Shift Mitigating for
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IJCV(129), No. 7, July 2021, pp. 2244-2263.
Springer DOI
2106
BibRef
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Riggan, B.S.[Benjamin S.],
Unsupervised Attention Based Instance Discriminative Learning for
Person Re-Identification,
WACV21(2421-2430)
IEEE DOI
2106
Annotations, Transfer learning,
Supervised learning, Lighting, Computer architecture
BibRef
Gu, H.Y.[Hong-Yang],
Fu, G.Y.[Guang-Yuan],
Wang, X.[Xu],
Zhu, J.[Jun],
Learning auto-scale representations for person re-identification,
IVC(112), 2021, pp. 104241.
Elsevier DOI
2107
Person re-identification, Auto-scale learning,
Neural architecture search, AutoML
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Uner, O.C.[Onur Can],
Aslan, C.[Cem],
Ercan, B.[Burak],
Ates, T.[Tayfun],
Celikcan, U.[Ufuk],
Erdem, A.[Aykut],
Erdem, E.[Erkut],
Synthetic18K: Learning Better Representations for Person Re-ID and
Attribute Recognition from 1.4 Million Synthetic Images,
SP:IC(97), 2021, pp. 116335.
Elsevier DOI
2107
Person re-identification, Attribute recognition, Synthetic data
BibRef
Yang, X.[Xi],
Liu, L.C.[Liang-Chen],
Wang, N.N.[Nan-Nan],
Gao, X.B.[Xin-Bo],
A Two-Stream Dynamic Pyramid Representation Model for Video-Based
Person Re-Identification,
IP(30), 2021, pp. 6266-6276.
IEEE DOI
2107
Video sequences, Sampling methods, Feature extraction,
Task analysis, Semantics, Measurement, two-stream network
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Liu, L.C.[Liang-Chen],
Yang, X.[Xi],
Wang, N.N.[Nan-Nan],
Gao, X.B.[Xin-Bo],
Frequency Information Disentanglement Network for Video-Based Person
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IP(32), 2023, pp. 4287-4298.
IEEE DOI
2308
Frequency-domain analysis, Task analysis, High frequency,
Pedestrians, Frequency conversion, Feature extraction,
feature disentanglement
BibRef
Yin, Q.Z.[Qing-Ze],
Wang, G.[Guan'an],
Ding, G.D.[Guo-Dong],
Gong, S.G.[Shao-Gang],
Tang, Z.M.[Zhen-Min],
Multi-View Label Prediction for Unsupervised Learning Person
Re-Identification,
SPLetters(28), 2021, pp. 1390-1394.
IEEE DOI
2108
Training, Trajectory, Noise measurement, Clustering algorithms,
Annotations, Merging, Cameras, Unsupervised learning,
clustering
BibRef
Shu, X.J.[Xiu-Jun],
Li, G.[Ge],
Wei, L.H.[Long-Hui],
Zhong, J.X.[Jia-Xing],
Zang, X.H.[Xiang-Hao],
Zhang, S.L.[Shi-Liang],
Wang, Y.W.[Yao-Wei],
Liang, Y.S.[Yong-Sheng],
Tian, Q.[Qi],
Diverse part attentive network for video-based person
re-identification,
PRL(149), 2021, pp. 17-23.
Elsevier DOI
2108
Person re-identification, Person retrieval, Self-attention
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Zang, X.H.[Xiang-Hao],
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Gao, W.[Wei],
Shu, X.J.[Xiu-Jun],
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IET-IPR(16), No. 3, 2022, pp. 729-741.
DOI Link
2202
BibRef
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Wang, Y.W.[Yao-Wei],
Zhang, S.L.[Shi-Liang],
Progressive Feature Enhancement for Person Re-Identification,
IP(30), 2021, pp. 8384-8395.
IEEE DOI
2110
Feature extraction, Visualization, Convolutional neural networks,
Training, Detectors, Robustness, Fuses, Person re-identification,
layer-specific supervision
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Kiran, M.[Madhu],
Bhuiyan, A.[Amran],
Nguyen-Meidine, L.T.[Le Thanh],
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IVC(113), 2021, pp. 104246.
Elsevier DOI
2108
Video surveillance, Person re-identification, Optical flow,
Metric learning, Attention mechanisms
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Bhuiyan, A.[Amran],
Liu, Y.[Yang],
Siva, P.[Parthipan],
Javan, M.[Mehrsan],
Ben Ayed, I.[Ismail],
Granger, E.[Eric],
Pose Guided Gated Fusion for Person Re-identification,
WACV20(2664-2673)
IEEE DOI
2006
Logic gates, Feature extraction, Measurement, Bones,
Machine learning, Benchmark testing
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Zhang, Z.Y.[Zi-Yue],
Jiang, S.[Shuai],
Huang, C.Z.T.[Cong-Zhen-Tao],
Li, Y.[Yang],
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RGB-IR cross-modality person ReID based on teacher-student GAN model,
PRL(150), 2021, pp. 155-161.
Elsevier DOI
2109
Person ReID, Cross-modality, Teacher-student model
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Wu, G.[Guile],
Zhu, X.T.[Xia-Tian],
Gong, S.G.[Shao-Gang],
Learning hybrid ranking representation for person re-identification,
PR(121), 2022, pp. 108239.
Elsevier DOI
2109
Person re-identification, Ranking representation, Ranking ensemble
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Li, Y.[Yaoyu],
Yao, H.T.[Han-Tao],
Xu, C.S.[Chang-Sheng],
TEST: Triplet Ensemble Student-Teacher Model for Unsupervised Person
Re-Identification,
IP(30), 2021, pp. 7952-7963.
IEEE DOI
2109
Adaptation models, Learning systems, Couplings, Training,
Knowledge engineering, Feature extraction, Predictive models, self-ensembling
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Sun, R.[Rui],
Liang, Q.L.[Qi-Li],
Yang, Z.[Zi],
Zhao, Z.H.[Zheng-Hui],
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IEICE(E104-D), No. 10, October 2021, pp. 1775-1779.
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2110
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Shao, Z.F.[Zhen-Feng],
Wang, J.M.[Jia-Ming],
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Huang, X.[Xiao],
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Internal and external spatial-temporal constraints for person
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JVCIR(80), 2021, pp. 103302.
Elsevier DOI
2110
Person reidentification, Convolution neural network,
Attention mechanism, Spatial-temporal constraint
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Wang, B.Q.[Bin-Quan],
Ma, G.Q.[Guo-Qi],
Zhu, M.[Ming],
Fast Momentum Contrast Learning for Unsupervised Person
Re-Identification,
SPLetters(28), 2021, pp. 2073-2077.
IEEE DOI
2111
Training, Dictionaries, Visualization, Feature extraction, Cameras,
Supervised learning, Convolutional neural networks,
representation learning
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Raj, S.S.[S. Sridhar],
Prasad, M.V.N.K.[Munaga V.N.K.],
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Spatio-Temporal association rule based deep annotation-free
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Elsevier DOI
2112
Unsupervised person re-identification, Clustering, Labeling,
Spatio-temporal, Deep learning
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Zhang, C.Y.[Chen-Yang],
Tang, Y.Q.[Yong-Qiang],
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Yang, X.B.[Xue-Bing],
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Improving Domain-Adaptive Person Re-Identification by Dual-Alignment
Learning With Camera-Aware Image Generation,
CirSysVideo(31), No. 11, November 2021, pp. 4334-4346.
IEEE DOI
2112
Cameras, Training, Data models, Correlation, Clustering algorithms,
Adaptation models, Prediction algorithms,
mutual information
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Cheng, G.[Guoan],
Shi, J.Y.[Jun-Yu],
Wang, H.[Hao],
Chen, L.[Long],
Guo, J.X.[Jia-Xi],
Wang, S.K.[Sheng-Ke],
A Study on Pedestrian Re-identification Based on Transfer Learning,
ICIVC21(112-118)
IEEE DOI
2112
Training, Target recognition, Transfer learning,
Feature extraction, Video surveillance, Probabilistic logic,
motion trajectory
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Wei, W.Y.[Wen-Yu],
Yang, W.Z.[Wen-Zhong],
Zuo, E.[Enguang],
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IET-Bio(11), No. 1, 2022, pp. 23-34.
DOI Link
2112
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Zhuang, Z.J.[Zi-Jie],
Wei, L.H.[Long-Hui],
Xie, L.X.[Ling-Xi],
Ai, H.Z.[Hai-Zhou],
Tian, Q.[Qi],
Camera-Based Batch Normalization: An Effective Distribution Alignment
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CirSysVideo(32), No. 1, January 2022, pp. 374-387.
IEEE DOI
2201
Cameras, Task analysis, Training, Annotations, Testing, Visualization,
Feature extraction, Person re-identification, distribution gap,
cross-modality tasks
BibRef
Zhuang, Z.J.[Zi-Jie],
Wei, L.H.[Long-Hui],
Xie, L.X.[Ling-Xi],
Zhang, T.Y.[Tian-Yu],
Zhang, H.H.[Heng-Heng],
Wu, H.Z.[Hao-Zhe],
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Tian, Q.[Qi],
Rethinking the Distribution Gap of Person Re-identification with
Camera-Based Batch Normalization,
ECCV20(XII: 140-157).
Springer DOI
2010
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Wei, W.Y.[Wen-Yu],
Yang, W.Z.[Wen-Zhong],
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Wang, L.H.[Li-Hua],
Person re-identification based on deep learning: An overview,
JVCIR(82), 2022, pp. 103418.
Elsevier DOI
2201
Person re-identification, Deep learning,
Convolutional neural networks, Attention mechanism
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Shao, J.[Jie],
Ma, X.Y.[Xiao-Yu],
Hierarchical Pseudo Labeling Based Embranchment Learning for One-Shot
Person Re-Identification,
SPLetters(29), 2022, pp. 434-438.
IEEE DOI
2202
Artificial neural networks, Training, Feature extraction,
Task analysis, Labeling, Data mining, Reliability, Center Loss,
one-shot person re-ID
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Gong, X.[Xun],
Yao, Z.[Zu],
Li, X.[Xin],
Fan, Y.[Yueqiao],
Luo, B.[Bin],
Fan, J.F.[Jian-Feng],
Lao, B.[Boji],
LAG-Net: Multi-Granularity Network for Person Re-Identification via
Local Attention System,
MultMed(24), 2022, pp. 217-229.
IEEE DOI
2202
Feature extraction, Semantics, Pose estimation, Task analysis, Fans,
Visualization, Fuses, Person re-identification, local attention,
deep learning
BibRef
Li, Y.[Yaoyu],
Yao, H.T.[Han-Tao],
Xu, C.S.[Chang-Sheng],
Intra-Domain Consistency Enhancement for Unsupervised Person
Re-Identification,
MultMed(24), 2022, pp. 415-425.
IEEE DOI
2202
Ice, Collaboration, Adaptation models, Training, Cameras,
Pattern recognition, Noise measurement, Person re-identification,
unsupervised domain adaptation
BibRef
Yang, X.F.[Xiao-Feng],
Wang, Q.S.[Qian-Shan],
Li, W.K.[Wen-Kuan],
Zhou, Z.H.[Zi-Hao],
Li, H.F.[Hai-Fang],
Unsupervised Domain Adaptation Pedestrian Re-Identification Based on
an Improved Dissimilarity Space,
IVC(118), 2022, pp. 104354.
Elsevier DOI
2202
Transfer learning, Cross-domain, Pedestrian re-identification,
Maximum mean discrepancy, Dissimilarity space
BibRef
Wang, W.H.[Wen-Hao],
Zhao, F.[Fang],
Liao, S.C.[Sheng-Cai],
Shao, L.[Ling],
Attentive WaveBlock: Complementarity-Enhanced Mutual Networks for
Unsupervised Domain Adaptation in Person Re-Identification and Beyond,
IP(31), 2022, pp. 1532-1544.
IEEE DOI
2202
Task analysis, Neural networks, Clustering algorithms,
Adaptation models, Training, Pipelines, Reliability,
attentive WaveBlock
BibRef
Lu, J.J.[Jian-Jie],
Zhang, W.D.[Wei-Dong],
Yin, H.B.[Hai-Bing],
Generate and Purify:
Efficient Person Data Generation for Re-Identification,
MultMed(24), 2022, pp. 558-566.
IEEE DOI
2202
Training, Convolutional codes, Data models, Image synthesis,
Heating systems, Generative adversarial networks, Training data,
re-identification
BibRef
Ming, Z.Q.[Zhang-Qiang],
Zhu, M.[Min],
Wang, X.K.[Xiang-Kun],
Zhu, J.[Jiamin],
Cheng, J.L.[Jun-Long],
Gao, C.R.[Cheng-Rui],
Yang, Y.[Yong],
Wei, X.Y.[Xiao-Yong],
Deep learning-based person re-identification methods:
A survey and outlook of recent works,
IVC(119), 2022, pp. 104394.
Elsevier DOI
2202
Survey, Re-Identification. Person re-identification, Deep metric learning,
Local feature learning, Generative adversarial learning,
Sequence feature learning
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Si, T.Z.[Tong-Zhen],
He, F.Z.[Fa-Zhi],
Wu, H.R.[Hao-Ran],
Duan, Y.S.[Yan-Song],
Spatial-Driven Features Based on Image Dependencies for Person
Re-Identification,
PR(124), 2022, pp. 108462.
Elsevier DOI
2203
Person re-identification, Spatial dependencies,
Recurrent neural network, Deep learning
BibRef
Gu, H.Y.[Hong-Yang],
Li, J.M.[Jian-Min],
Fu, G.Y.[Guang-Yuan],
Yue, M.[Min],
Zhu, J.[Jun],
Loss function search for person re-identification,
PR(124), 2022, pp. 108432.
Elsevier DOI
2203
Person re-identification, Margin-based softmax loss,
Loss function search, AutoML
BibRef
Gu, H.Y.[Hong-Yang],
Li, J.M.[Jian-Min],
Fu, G.Y.[Guang-Yuan],
Wong, C.[Chifong],
Chen, X.H.[Xing-Hao],
Zhu, J.[Jun],
AutoLoss-GMS: Searching Generalized Margin-based Softmax Loss
Function for Person Re-identification,
CVPR22(4734-4743)
IEEE DOI
2210
Protocols, Computational modeling, Evolutionary computation,
Pattern recognition, Task analysis, Recognition: detection,
Vision applications and systems
BibRef
Li, Q.[Qing],
Peng, X.J.[Xiao-Jiang],
Qiao, Y.[Yu],
Hao, Q.[Qi],
Unsupervised person re-identification with multi-label learning
guided self-paced clustering,
PR(125), 2022, pp. 108521.
Elsevier DOI
2203
MLC, Multi-scale network, Multi-label learning,
Self-paced clustering, Unsupervised person Re-ID
BibRef
Lu, Y.C.[Yi-Chen],
Deng, W.H.[Wei-Hong],
Transferring discriminative knowledge via connective momentum
clustering on person re-identification,
PR(126), 2022, pp. 108569.
Elsevier DOI
2204
Person re-identification, Unsupervised domain adaptation,
Graph convolutional networks, Momentum mechanism, Batch normalization
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Chen, Y.F.[Yi-Fan],
Wang, H.[Han],
Sun, X.L.[Xiao-Lu],
Fan, B.[Bin],
Tang, C.[Chu],
Zeng, H.[Hui],
Deep attention aware feature learning for person re-Identification,
PR(126), 2022, pp. 108567.
Elsevier DOI
2204
Person re-identification, Attention learning, Multi-task learning
BibRef
Ye, M.[Mang],
Shen, J.B.[Jian-Bing],
Lin, G.J.[Gao-Jie],
Xiang, T.[Tao],
Shao, L.[Ling],
Hoi, S.C.H.[Steven C. H.],
Deep Learning for Person Re-Identification: A Survey and Outlook,
PAMI(44), No. 6, June 2022, pp. 2872-2893.
IEEE DOI
2205
Survey, Re-Identification. Annotations, Cameras, Training, Training data, Feature extraction,
Data models, Deep learning, Person re-identification,
deep learning
BibRef
Gong, J.H.[Jia-Hao],
Zhao, S.[Sanyuan],
Lam, K.M.[Kin-Man],
Gao, X.[Xin],
Shen, J.B.[Jian-Bing],
Spectrum-irrelevant fine-grained representation for visible-infrared
person re-identification,
CVIU(232), 2023, pp. 103703.
Elsevier DOI
2305
Visible-infrared person re-identification
BibRef
Liu, C.[Chuang],
Yang, H.[Hua],
Zhou, Q.[Qin],
Zheng, S.[Shibao],
Making person search enjoy the merits of person re-identification,
PR(127), 2022, pp. 108654.
Elsevier DOI
2205
Person search, Person re-identification, Knowledge transfer,
Teacher-guided disentangling network, Context ranking
BibRef
Zheng, D.Y.[Ding-Yuan],
Xiao, J.[Jimin],
Chen, K.[Ke],
Huang, X.W.[Xiao-Wei],
Chen, L.[Lin],
Zhao, Y.[Yao],
Soft pseudo-Label shrinkage for unsupervised domain adaptive person
re-identification,
PR(127), 2022, pp. 108615.
Elsevier DOI
2205
Person re-identification, Unsupervised domain adaptation,
Clustering algorithms, Label noise, Soft pseudo-labels
BibRef
Huang, N.Z.[Nian-Zchang],
Liu, K.L.[Kun-Long],
Liu, Y.[Yang],
Zhang, Q.[Qiang],
Han, J.G.[Jun-Gong],
Cross-modality person re-identification via multi-task learning,
PR(128), 2022, pp. 108653.
Elsevier DOI
2205
Cross-modality person re-identification,
Person body information, Multi-task learning
BibRef
Yang, W.P.[Wei-Ping],
Zhang, D.[De],
Unsupervised person re-identification by part-compensated soft
multi-label learning,
IET-IPR(16), No. 7, 2022, pp. 2012-2024.
DOI Link
2205
BibRef
Chen, Y.[Ying],
Xia, S.X.[Shi-Xiong],
Zhao, J.Q.[Jia-Qi],
Zhou, Y.[Yong],
Niu, Q.[Qiang],
Yao, R.[Rui],
Zhu, D.J.[Dong-Jun],
Liu, D.J.[Dong-Jingdian],
ResT-ReID: Transformer block-based residual learning for person
re-identification,
PRL(157), 2022, pp. 90-96.
Elsevier DOI
2205
Person re-identification, Vision transformer,
Graph convolution networks, Self-attention strategy
BibRef
Huang, Y.[Yewen],
Lian, S.C.[Si-Cheng],
Hu, H.F.[Hai-Feng],
AVPL: Augmented visual perception learning for person
Re-identification and beyond,
PR(129), 2022, pp. 108736.
Elsevier DOI
2206
Person Re-identification,
Augmented visual perception learning, Batch attention, Two-stream hypothesis
BibRef
Li, M.K.[Ming-Kun],
Sun, H.[He],
Lin, C.[Chaoqun],
Li, C.G.[Chun-Guang],
Guo, J.[Jun],
The devil in the tail: Cluster consolidation plus cluster adaptive
balancing loss for unsupervised person re-identification,
PR(129), 2022, pp. 108763.
Elsevier DOI
2206
Unsupervised person re-identification, Cluster consolidation,
Cluster adaptive balancing loss, Long-tail problem
BibRef
Yin, J.H.[Jun-Hui],
Xie, J.Y.[Ji-Yang],
Ma, Z.Y.[Zhan-Yu],
Guo, J.[Jun],
MPCCL: Multiview predictive coding with contrastive learning for
person re-identification,
PR(129), 2022, pp. 108710.
Elsevier DOI
2206
Person re-identification, Kernel density estimation,
Representation construction, Contrastive learning
BibRef
Yao, Y.M.[Ying-Mao],
Jiang, X.Y.[Xiao-Yan],
Fujita, H.[Hamido],
Fang, Z.J.[Zhi-Jun],
A sparse graph wavelet convolution neural network for video-based
person re-identification,
PR(129), 2022, pp. 108708.
Elsevier DOI
2206
Video-based person re-identification, Weighted sparse graph,
Graph wavelet convolution neural network
BibRef
Li, M.K.[Ming-Kun],
Li, C.G.[Chun-Guang],
Guo, J.[Jun],
Cluster-Guided Asymmetric Contrastive Learning for Unsupervised
Person Re-Identification,
IP(31), 2022, pp. 3606-3617.
IEEE DOI
2206
Image color analysis, Training, Proposals, Representation learning,
Neural networks, Gray-scale, Measurement, cluster refinement
BibRef
Bai, S.T.[Shu-Tao],
Ma, B.P.[Bing-Peng],
Chang, H.[Hong],
Huang, R.[Rui],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
SANet: Statistic Attention Network for Video-Based Person
Re-Identification,
CirSysVideo(32), No. 6, June 2022, pp. 3866-3879.
IEEE DOI
2206
Feature extraction, Task analysis, Computational modeling,
Visualization, Video sequences, Fuses, Computer science,
high-order statistics
BibRef
Huang, Z.H.[Zong-Heng],
He, B.T.[Bo-Tao],
Yang, B.[Bo],
Gao, C.X.[Chang-Xin],
Sang, N.[Nong],
Norm-Aware Margin Assignment for Person Re-Identification,
SPLetters(29), 2022, pp. 1292-1296.
IEEE DOI
2206
Training, Image quality, Measurement, Correlation, Visualization,
Feature extraction, Benchmark testing, Deep learning, metric learning
BibRef
Chen, Y.[Yiyu],
Fan, Z.[Zheyi],
Chen, S.[Shuni],
Consistent camera-invariant and noise-tolerant learning for
unsupervised person re-identification,
IVC(123), 2022, pp. 104462.
Elsevier DOI
2206
Person re-identification, Meta learning, Noise pseudo label, Camera variations
BibRef
Zhang, F.P.[Fu-Ping],
Zhang, T.Z.[Tian-Zhao],
Sun, R.X.[Ruo-Xi],
Huang, C.[Chao],
Wei, J.M.[Jian-Ming],
An Efficient Axial-Attention Network for Video-Based Person
Re-Identification,
SPLetters(29), 2022, pp. 1352-1356.
IEEE DOI
2206
Transforms, Sun, Feature extraction, Computational efficiency,
Computational complexity, Transformers, Spatial resolution, pyramid pooling
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Song, X.[Xulin],
Jin, Z.[Zhong],
Robust Label Rectifying With Consistent Contrastive-Learning for
Domain Adaptive Person Re-Identification,
MultMed(24), 2022, pp. 3229-3239.
IEEE DOI
2207
Noise measurement, Training, Feature extraction, Uncertainty,
Reliability, Estimation, Clustering algorithms,
person Re-ID
BibRef
Liu, T.Y.[Tian-Yang],
Lin, Y.[Yutian],
Du, B.[Bo],
Unsupervised Person Re-Identification With Stochastic Training
Strategy,
IP(31), 2022, pp. 4240-4250.
IEEE DOI
2207
Cameras, Training, Stochastic processes, Feature extraction,
Task analysis, Noise measurement, Pipelines,
contrastive learning
BibRef
Yang, F.[Fan],
Li, W.[Wei],
Liang, B.B.[Bin-Bin],
Han, S.C.[Song-Chen],
Zhu, X.[Xuan],
Multi-stage attention network for video-based person
re-identification,
IET-CV(16), No. 5, 2022, pp. 445-455.
DOI Link
2207
computer vision, image processing, object detection,
object tracking, pedestrians, video retrieval, video surveillance
BibRef
Cheng, D.Q.[De-Qiang],
Li, J.H.[Jia-Han],
Kou, Q.Q.[Qi-Qi],
Zhao, K.[Kai],
Liu, R.H.[Rui-Hang],
H-net: Unsupervised domain adaptation person re-identification
network based on hierarchy,
IVC(124), 2022, pp. 104493.
Elsevier DOI
2208
Unsupervised domain adaptation, Person re-identification,
Hierarchical, Hardest sample
BibRef
Wu, L.[Lin],
Liu, D.[Deyin],
Zhang, W.Y.[Wen-Ying],
Chen, D.P.[Da-Peng],
Ge, Z.Y.[Zong-Yuan],
Boussaid, F.[Farid],
Bennamoun, M.[Mohammed],
Shen, J.[Jialie],
Pseudo-Pair Based Self-Similarity Learning for Unsupervised Person
Re-Identification,
IP(31), 2022, pp. 4803-4816.
IEEE DOI
2208
Training, Unsupervised learning, Australia, Annotations, Convolution,
Cameras, Person re-identification, pseudo pair construction,
self-similarity learning
BibRef
Li, W.L.[Wan-Lu],
Zhang, Y.Z.[Yun-Zhou],
Shi, W.D.[Wei-Dong],
Coleman, S.[Sonya],
A CAM-Guided Parameter-Free Attention Network for Person
Re-Identification,
SPLetters(29), 2022, pp. 1559-1563.
IEEE DOI
2208
Feature extraction, Training, Convolution, Cameras, Data mining,
Covariance matrices, Computational modeling, parameter-free
BibRef
Liu, Y.X.[Yi-Xiu],
Zhang, Y.Z.[Yun-Zhou],
Bhanu, B.[Bir],
Coleman, S.[Sonya],
Kerr, D.[Dermot],
Data Assimilation Network for Generalizable Person Re-Identification,
CirSysVideo(32), No. 8, August 2022, pp. 5536-5550.
IEEE DOI
2208
Data assimilation, Training, Adaptation models, Task analysis,
Estimation, Microstrip, Feature extraction,
progressive augmented memory
BibRef
Hu, W.P.[Wei-Peng],
Liu, B.[Bohong],
Zeng, H.[Haitang],
Hou, Y.[Yanke],
Hu, H.F.[Hai-Feng],
Adversarial Decoupling and Modality-Invariant Representation Learning
for Visible-Infrared Person Re-Identification,
CirSysVideo(32), No. 8, August 2022, pp. 5095-5109.
IEEE DOI
2208
Representation learning, Feature extraction, Task analysis,
Decorrelation, Cameras, Semantics, Lighting, orthogonal decorrelation
BibRef
Zhang, J.[Ji],
Ainam, J.P.[Jean-Paul],
Song, W.[Wenai],
Zhao, L.H.[Li-Hui],
Wang, X.[Xin],
Li, H.Z.[Hong-Zhou],
Learning global and local features using graph neural networks for
person re-identification,
SP:IC(107), 2022, pp. 116744.
Elsevier DOI
2208
Person re-identification, Body-part, Alignment, Graph neural networks
BibRef
Zheng, D.Y.[Ding-Yuan],
Xiao, J.[Jimin],
Wei, Y.C.[Yun-Chao],
Wang, Q.F.[Qiu-Feng],
Huang, K.[Kaizhu],
Zhao, Y.[Yao],
Unsupervised domain adaptation in homogeneous distance space for
person re-identification,
PR(132), 2022, pp. 108941.
Elsevier DOI
2209
Person re-identification, Unsupervised domain adaptation,
Distribution alignment, Clustering, Pseudo label
BibRef
Qin, W.C.[Wen-Cheng],
Huang, B.J.[Bao-Jin],
Qin, P.Z.[Pin-Zhong],
Huang, Z.Y.[Zhi-Yong],
Zhong, D.[Daidi],
Learning diverse and deep clues for person reidentification,
IVC(126), 2022, pp. 104551.
Elsevier DOI
2209
Attention network, convolutional neural network,
Grouped pyramid, Global feature, Local features, Person re-identification
BibRef
Huang, Y.K.[Yu-Kun],
Fu, X.Y.[Xue-Yang],
Li, L.[Liang],
Zha, Z.J.[Zheng-Jun],
Learning Degradation-Invariant Representation for Robust Real-World
Person Re-Identification,
IJCV(130), No. 11, November 2022, pp. 2770-2796.
Springer DOI
2210
BibRef
Huang, Y.K.[Yu-Kun],
Zha, Z.J.[Zheng-Jun],
Fu, X.Y.[Xue-Yang],
Hong, R.,
Li, L.[Liang],
Real-World Person Re-Identification via Degradation Invariance
Learning,
CVPR20(14072-14082)
IEEE DOI
2008
Degradation, Feature extraction, Lighting, Image resolution,
Task analysis, Image reconstruction, Image restoration
BibRef
Mao, Z.[Zhu],
Wang, X.[Xiao],
Xu, X.[Xin],
Wang, Z.[Zheng],
Lin, C.W.[Chia-Wen],
Continuous and Unified Person Re-Identification,
SPLetters(29), 2022, pp. 1983-1987.
IEEE DOI
2210
Task analysis, Training, Data models, Predictive models,
Optimization, Training data, Feature extraction, alternate learning
BibRef
Eom, C.[Chanho],
Lee, W.[Wonkyung],
Lee, G.[Geon],
Ham, B.[Bumsub],
Disentangled Representations for Short-Term and Long-Term Person
Re-Identification,
PAMI(44), No. 12, December 2022, pp. 8975-8991.
IEEE DOI
2212
Feature extraction, Task analysis, Clutter, Interpolation,
Image color analysis, Generative adversarial networks,
generative adversarial learning
BibRef
Xi, J.L.[Jia-Li],
Huang, J.Q.[Jian-Qiang],
Zheng, S.[Shibao],
Zhou, Q.[Qin],
Schiele, B.[Bernt],
Hua, X.S.[Xian-Sheng],
Sun, Q.[Qianru],
Learning comprehensive global features in person re-identification:
Ensuring discriminativeness of more local regions,
PR(134), 2023, pp. 109068.
Elsevier DOI
2212
Person re-identification, Baseline, Comprehensive
BibRef
Zhang, H.W.[Hong-Wei],
Zhang, G.Q.[Guo-Qing],
Chen, Y.H.[Yu-Hao],
Zheng, Y.H.[Yu-Hui],
Global Relation-Aware Contrast Learning for Unsupervised Person
Re-Identification,
CirSysVideo(32), No. 12, December 2022, pp. 8599-8610.
IEEE DOI
2212
Training, Cameras, Representation learning, Data models,
Computational modeling, Adaptation models, Information science,
representation learning
BibRef
Zhang, G.Q.[Guo-Qing],
Zhang, H.W.[Hong-Wei],
Lin, W.S.[Wei-Si],
Chandran, A.K.[Arun Kumar],
Jing, X.[Xuan],
Camera Contrast Learning for Unsupervised Person Re-Identification,
CirSysVideo(33), No. 8, August 2023, pp. 4096-4107.
IEEE DOI
2308
Cameras, Training, Feature extraction, Computational modeling,
Complexity theory, Integrated circuit modeling, Data models, similarity metric
BibRef
Xiang, J.[Jun],
Huang, Z.Y.[Zi-Yuan],
Jiang, X.P.[Xiao-Ping],
Hou, J.H.[Jian-Hua],
Similarity learning with deep CRF for person re-identification,
PR(135), 2023, pp. 109151.
Elsevier DOI
2212
Person re-identification, Deep learning,
Conditional random field (CRF), Group-wise similarities
BibRef
Zhao, Y.[Yu],
Shu, Q.Y.[Qiao-Yuan],
Shi, X.[Xi],
Dual-level contrastive learning for unsupervised person
re-identification,
IVC(129), 2023, pp. 104607.
Elsevier DOI
2301
Unsupervised person re-ID, Instance discrimination,
Unsupervised feature learning, Contrastive learning
BibRef
Zhao, Y.[Yu],
Shu, Q.Y.[Qiao-Yuan],
Shi, X.[Xi],
Zhan, J.[Jian],
Unsupervised person re-identification by dynamic hybrid contrastive
learning,
IVC(137), 2023, pp. 104786.
Elsevier DOI
2309
Unsupervised person re-identification, Contrastive learning,
Intra-category similarity, Inter-instance discrimination
BibRef
Zhang, Y.F.[Yi-Fan],
Zhang, Z.[Zhang],
Li, D.[Da],
Jia, Z.[Zhen],
Wang, L.[Liang],
Tan, T.N.[Tie-Niu],
Learning Domain Invariant Representations for Generalizable Person
Re-Identification,
IP(32), 2023, pp. 509-523.
IEEE DOI
2301
Data models, Correlation, Adaptation models, Training, Feature extraction,
Analytical models, Representation learning, backdoor adjustment
BibRef
Verma, A.[Astha],
Subramanyam, A.V.,
Wang, Z.[Zheng],
Satoh, S.[Shin'ichi],
Shah, R.R.[Rajiv Ratn],
Unsupervised Domain Adaptation for Person Re-Identification Via
Individual-Preserving and Environmental-Switching Cyclic Generation,
MultMed(25), 2023, pp. 364-377.
IEEE DOI
2302
Adaptation models, Cameras, Training, Data models, Task analysis,
Generative adversarial networks, Feature extraction, GAN
BibRef
Zhang, Z.[Zhong],
Dong, Q.[Qing],
Wang, S.[Sen],
Liu, S.[Shuang],
Xiao, B.H.[Bai-Hua],
Durrani, T.S.[Tariq S.],
Cross-modality person re-identification using hybrid mutual learning,
IET-CV(17), No. 1, 2023, pp. 1-12.
DOI Link
2303
BibRef
He, D.[Di],
Zhang, J.R.[Jing-Rui],
Zhang, Z.[Zhong],
Liu, S.[Shuang],
Durrani, T.S.[Tariq S.],
Integration graph attention network and multi-centre constrained loss
for cross-modality person re-identification,
IET-CV(17), No. 1, 2023, pp. 76-87.
DOI Link
2303
BibRef
Peng, J.J.[Jin-Jia],
Yu, J.Z.[Jia-Zuo],
Jiang, G.Q.[Guang-Qi],
Wang, H.B.[Hui-Bing],
Qi, J.[Jing],
Joint learning with diverse knowledge for re-identification,
SP:IC(113), 2023, pp. 116922.
Elsevier DOI
2303
Diversity knowledge, Joint learning, Re-identification
BibRef
Yang, F.X.[Feng-Xiang],
Weng, J.J.[Juan-Juan],
Zhong, Z.[Zhun],
Liu, H.[Hong],
Wang, Z.[Zheng],
Luo, Z.M.[Zhi-Ming],
Cao, D.L.[Dong-Lin],
Li, S.Z.[Shao-Zi],
Satoh, S.[Shin'ichi],
Sebe, N.[Nicu],
Towards Robust Person Re-Identification by Defending Against
Universal Attackers,
PAMI(45), No. 4, April 2023, pp. 5218-5235.
IEEE DOI
2303
Training, Perturbation methods, Adaptation models, Robustness,
Task analysis, Resists, Generators, Person Re-Identification,
Meta-Learning
BibRef
Yang, F.X.[Feng-Xiang],
Zhong, Z.[Zhun],
Luo, Z.M.[Zhi-Ming],
Cai, Y.Z.[Yuan-Zheng],
Lin, Y.J.[Yao-Jin],
Li, S.Z.[Shao-Zi],
Sebe, N.[Nicu],
Joint Noise-Tolerant Learning and Meta Camera Shift Adaptation for
Unsupervised Person Re-Identification,
CVPR21(4853-4862)
IEEE DOI
2111
Training, Adaptation models, Heuristic algorithms,
Clustering algorithms, Training data, Resists, Cameras
BibRef
Zhao, Y.Y.[Yu-Yang],
Zhong, Z.[Zhun],
Yang, F.X.[Feng-Xiang],
Luo, Z.M.[Zhi-Ming],
Lin, Y.J.[Yao-Jin],
Li, S.Z.[Shao-Zi],
Sebe, N.[Nicu],
Learning to Generalize Unseen Domains via Memory-based Multi-Source
Meta-Learning for Person Re-Identification,
CVPR21(6273-6282)
IEEE DOI
2111
Training, Data privacy, Computational modeling,
Benchmark testing, Data models, Pattern recognition
BibRef
Chen, F.[Feng],
Wang, N.[Nian],
Tang, J.[Jun],
Yan, P.[Pu],
Yu, J.[Jun],
Unsupervised person re-identification via multi-domain joint learning,
PR(138), 2023, pp. 109369.
Elsevier DOI
2303
Person re-identification, Data augmentation, Domain adaptation,
Unsupervised learning
BibRef
Bukhari, M.[Maryam],
Yasmin, S.[Sadaf],
Naz, S.[Sheneela],
Maqsood, M.[Muazzam],
Rew, J.[Jehyeok],
Rho, S.[Seungmin],
Language and vision based person re-identification for surveillance
systems using deep learning with LIP layers,
IVC(132), 2023, pp. 104658.
Elsevier DOI
2303
Person re-identification, Surveillance,
Language and vision based Re-ID, Deep learning
BibRef
Yin, J.H.[Jun-Hui],
Zhang, X.Y.[Xin-Yu],
Ma, Z.Y.[Zhan-Yu],
Guo, J.[Jun],
Liu, Y.[Yifan],
A Real-Time Memory Updating Strategy for Unsupervised Person
Re-Identification,
IP(32), 2023, pp. 2309-2321.
IEEE DOI
2305
Clustering algorithms, Training, Real-time systems,
Feature extraction, Representation learning, memory bank
BibRef
Cao, M.[Min],
Ding, C.[Cong],
Chen, C.[Chen],
Dou, H.[Hao],
Hu, X.[Xiyuan],
Yan, J.C.[Jun-Chi],
Progressive Context-Aware Graph Feature Learning for Target
Re-Identification,
MultMed(25), 2023, pp. 1230-1242.
IEEE DOI
2305
Feature extraction, Representation learning, Task analysis,
Message passing, Data mining, Semantics, Context modeling,
graph feature learning
BibRef
Chen, H.[Hao],
Wang, Y.[Yaohui],
Lagadec, B.[Benoit],
Dantcheva, A.[Antitza],
Bremond, F.[Francois],
Learning Invariance From Generated Variance for Unsupervised Person
Re-Identification,
PAMI(45), No. 6, June 2023, pp. 7494-7508.
IEEE DOI
2305
Image color analysis, Cameras, Shape, Lighting, Generators,
Generative adversarial networks, Contrastive learning,
representation disentanglement
BibRef
Zhao, J.[Jing],
Liao, J.[Jie],
Yuan, J.[Jin],
HSP-MFL: A High-level Semantic Property driven Multi-task Feature
Learning Network for unsupervised person Re-ID,
JVCIR(93), 2023, pp. 103828.
Elsevier DOI
2305
Unsupervised person re-identification, Multi-task learning,
Feature fusion, Discriminative feature learning
BibRef
Wang, D.W.[Deng-Wen],
Chen, Y.B.[Yan-Bing],
Wang, W.M.[Wang-Meng],
Tie, Z.X.[Zhi-Xin],
Fang, X.[Xian],
Ke, W.[Wei],
Uncertainty-guided joint attention and contextual relation network
for person re-identification,
JVCIR(93), 2023, pp. 103822.
Elsevier DOI
2305
Person re-identification, Uncertainty-guided joint attention,
Contextual relation network, Relation between features, Attention mechanism
BibRef
Liu, Q.[Qiang],
He, X.H.[Xiao-Hai],
Teng, Q.Z.[Qi-Zhi],
Qing, L.[Linbo],
Chen, H.G.[Hong-Gang],
BDNet: A BERT-based dual-path network for text-to-image cross-modal
person re-identification,
PR(141), 2023, pp. 109636.
Elsevier DOI
2306
Person re-identification, Image-text retrieval, Cross-modality, Attention
BibRef
Lan, L.[Long],
Teng, X.[Xiao],
Zhang, J.[Jing],
Zhang, X.[Xiang],
Tao, D.C.[Da-Cheng],
Learning to Purification for Unsupervised Person Re-Identification,
IP(32), 2023, pp. 3338-3353.
IEEE DOI
2307
Adaptation models, Training, Purification, Noise measurement,
Clustering algorithms, Task analysis, Unsupervised learning,
unsupervised person ReID
BibRef
Zheng, D.Y.[Ding-Yuan],
Xiao, J.[Jimin],
Sun, M.J.[Ming-Jie],
Bai, H.H.[Hui-Hui],
Hou, J.H.[Jun-Hui],
Plausible Proxy Mining With Credibility for Unsupervised Person
Re-Identification,
CirSysVideo(33), No. 7, July 2023, pp. 3308-3318.
IEEE DOI
2307
Cameras, Impurities, Training, Feature extraction, Visualization,
Task analysis, Annotations, Person re-identification, supervision signals
BibRef
Ma, H.Y.[Hao-Yan],
Li, X.[Xiang],
Yuan, X.[Xia],
Zhao, C.X.[Chun-Xia],
Denseformer: A dense transformer framework for person
re-identification,
IET-CV(17), No. 5, 2023, pp. 527-536.
DOI Link
2309
BibRef
Zhu, S.D.[Shang-Dong],
Zhang, Y.Z.[Yun-Zhou],
Feng, Y.[Yu],
GW-net: An efficient grad-CAM consistency neural network with
weakening of random erasing features for semi-supervised person
re-identification,
IVC(137), 2023, pp. 104790.
Elsevier DOI
2309
Semi-supervised person re-identification,
Grad-CAM consistency regularization module, Data augmentation
BibRef
Zhou, Y.H.[Yun-Hao],
Wang, Y.[Yi],
Chau, L.P.[Lap-Pui],
Moving Towards Centers: Re-Ranking With Attention and Memory for
Re-Identification,
MultMed(25), 2023, pp. 3456-3468.
IEEE DOI
2309
BibRef
Yang, K.[Kaiwen],
Tian, X.[Xinmei],
Domain-Class Correlation Decomposition for Generalizable Person
Re-Identification,
MultMed(25), 2023, pp. 3386-3396.
IEEE DOI
2309
BibRef
Huang, Z.Y.[Zhi-Yong],
Qin, P.[Pinzhong],
Yu, Z.[Zhi],
Tahsin, L.[Lamia],
Wang, M.Y.[Meng-Yao],
Liu, M.[Man],
Transformer-based feature interactor for person re-identification
with margin self-punishment loss,
IVC(137), 2023, pp. 104752.
Elsevier DOI
2309
Person re-identification, Attention mechanism,
Representation learning, Transformer
BibRef
Wang, D.[Dengwen],
Chen, Y.B.[Yan-Bing],
Tao, L.B.[Ling-Bing],
Hu, C.[Chentao],
Tie, Z.X.[Zhi-Xin],
Ke, W.[Wei],
AEA-Net: Affinity-supervised entanglement attentive network for person
re-identification,
PRL(172), 2023, pp. 237-244.
Elsevier DOI
2309
Person re-identification, Affinity-supervised attention,
Affinity relationship, Tangle hybrid loss
BibRef
Wang, K.[Kan],
Hu, S.P.[Shu-Ping],
Cheng, J.[Jun],
Cheng, J.[Jun],
Pang, J.X.[Jian-Xin],
Tan, H.[Huan],
RA Loss: Relation-Aware Loss for Robust Person Re-identification,
ACCV22(II:373-390).
Springer DOI
2307
BibRef
Su, P.[Peng],
Liu, R.[Rui],
Dong, J.[Jing],
Yi, P.F.[Peng-Fei],
Zhou, D.S.[Dong-Sheng],
Scfnet: A Spatial-channel Features Network Based on Heterocentric
Sample Loss for Visible-infrared Person Re-identification,
ACCV22(II:543-559).
Springer DOI
2307
BibRef
Das, N.[Nilaksh],
Peng, S.[ShengYun],
Chau, D.H.[Duen Horng],
Skelevision: Towards Adversarial Resiliency of Person Tracking with
Multi-task Learning,
AdvRob22(449-466).
Springer DOI
2304
BibRef
Zunino, A.[Andrea],
Murray, C.[Christopher],
Blythman, R.[Richard],
Murino, V.[Vittorio],
Which Expert Knows Best? Modulating Soft Learning with Online Batch
Confidence for Domain Adaptive Person Re-identification,
RealWorld22(594-607).
Springer DOI
2304
BibRef
Li, J.C.[Jia-Chen],
Wang, M.L.[Meng-Lin],
Gong, X.J.[Xiao-Jin],
Transformer Based Multi-Grained Features for Unsupervised Person
Re-Identification,
RealWorld23(1-9)
IEEE DOI
2302
Codes, Conferences, Network architecture, Feature extraction, Transformers
BibRef
Guo, J.W.[Jing-Wen],
Liu, H.[Hong],
Shi, W.[Wei],
Tang, H.[Hao],
Wu, J.B.[Jian-Bing],
Unsupervised Domain Adaptation Person Re-Identification by
Camera-Aware Style Decoupling and Uncertainty Modeling,
ICIP22(761-765)
IEEE DOI
2211
Representation learning, Adaptation models, Uncertainty,
Estimation, Network architecture, Benchmark testing, Cameras,
uncertainty estimation
BibRef
Sun, J.[Jia],
Li, Y.F.[Yan-Feng],
Chen, H.[Houjin],
Peng, Y.H.[Ya-Hui],
A Person Re-Identification Baseline Based on Attention Block Neural
Architecture Search,
ICIP22(841-845)
IEEE DOI
2211
Codes, Cameras, Convolutional neural networks, Task analysis,
Periodic structures, person re-identification, neural architecture search
BibRef
Zhang, P.Y.[Peng-Yi],
Dou, H.Z.[Huan-Zhang],
Yu, Y.L.[Yun-Long],
Li, X.[Xi],
Adaptive Cross-Domain Learning for Generalizable Person
Re-identification,
ECCV22(XIV:215-232).
Springer DOI
2211
BibRef
Jiao, B.L.[Bing-Liang],
Liu, L.Q.[Ling-Qiao],
Gao, L.Y.[Li-Ying],
Lin, G.S.[Guo-Sheng],
Yang, L.[Lu],
Zhang, S.Z.[Shi-Zhou],
Wang, P.[Peng],
Zhang, Y.N.[Yan-Ning],
Dynamically Transformed Instance Normalization Network for
Generalizable Person Re-Identification,
ECCV22(XIV:285-301).
Springer DOI
2211
BibRef
Xu, B.Q.[Bo-Qiang],
Liang, J.[Jian],
He, L.X.[Ling-Xiao],
Sun, Z.A.[Zhen-An],
Mimic Embedding via Adaptive Aggregation: Learning Generalizable Person
Re-identification,
ECCV22(XIV:372-388).
Springer DOI
2211
BibRef
Zhu, K.[Kuan],
Guo, H.Y.[Hai-Yun],
Yan, T.Y.[Tian-Yi],
Zhu, Y.S.[You-Song],
Wang, J.Q.[Jin-Qiao],
Tang, M.[Ming],
PASS: Part-Aware Self-Supervised Pre-Training for Person
Re-Identification,
ECCV22(XIV:198-214).
Springer DOI
2211
BibRef
Shuai, B.[Bing],
Li, X.Y.[Xin-Yu],
Kundu, K.[Kaustav],
Tighe, J.[Joseph],
Id-Free Person Similarity Learning,
CVPR22(14669-14679)
IEEE DOI
2210
Training, Representation learning, Target tracking, Costs,
Annotations, Pattern recognition,
Representation learning
BibRef
Zhu, H.W.[Hao-Wei],
Ke, W.J.[Wen-Jing],
Li, D.[Dong],
Liu, J.[Ji],
Tian, L.[Lu],
Shan, Y.[Yi],
Dual Cross-Attention Learning for Fine-Grained Visual Categorization
and Object Re-Identification,
CVPR22(4682-4692)
IEEE DOI
2210
Deep learning, Visualization, Image recognition,
Benchmark testing, Transformers,
Deep learning architectures and techniques
BibRef
Ni, H.[Hao],
Song, J.[Jingkuan],
Luo, X.P.[Xiao-Peng],
Zheng, F.[Feng],
Li, W.[Wen],
Shen, H.T.[Heng Tao],
Meta Distribution Alignment for Generalizable Person
Re-Identification,
CVPR22(2477-2486)
IEEE DOI
2210
Training, Adaptation models, Codes, Machine vision,
Computational modeling, Benchmark testing,
Self- semi- meta- Transfer/low-shot/long-tail learning
BibRef
Fu, D.P.[Deng-Pan],
Chen, D.D.[Dong-Dong],
Yang, H.[Hao],
Bao, J.M.[Jian-Min],
Yuan, L.[Lu],
Zhang, L.[Lei],
Li, H.Q.[Hou-Qiang],
Wen, F.[Fang],
Chen, D.[Dong],
Large-Scale Pre-training for Person Re-identification with Noisy
Labels,
CVPR22(01-11)
IEEE DOI
2210
Computational modeling, Machine vision, Prototypes, Manuals,
Performance gain, Pattern recognition, Noise measurement,
Self- semi- meta- unsupervised learning
BibRef
Wu, W.[Wei],
Liu, J.W.[Jia-Wei],
Zheng, K.[Kecheng],
Sun, Q.[Qibin],
Zha, Z.[ZhengJun],
Temporal Complementarity-Guided Reinforcement Learning for
Image-to-Video Person Re-Identification,
CVPR22(7309-7318)
IEEE DOI
2210
Representation learning, Uncertainty, Measurement uncertainty,
Reinforcement learning, Detectors, Markov processes,
Video analysis and understanding
BibRef
Cho, Y.[Yoonki],
Kim, W.J.[Woo Jae],
Hong, S.[Seunghoon],
Yoon, S.E.[Sung-Eui],
Part-based Pseudo Label Refinement for Unsupervised Person
Re-identification,
CVPR22(7298-7308)
IEEE DOI
2210
Representation learning, Smoothing methods, Codes, Machine vision,
Benchmark testing, Reliability engineering,
Vision applications and systems
BibRef
Wang, H.C.[Hao-Chen],
Shen, J.Y.[Jia-Yi],
Liu, Y.[Yongtuo],
Gao, Y.[Yan],
Gavves, E.[Efstratios],
NFormer: Robust Person Re-identification with Neighbor Transformer,
CVPR22(7287-7297)
IEEE DOI
2210
Representation learning, Training, Codes, Computational modeling,
Focusing, Interference, Recognition: detection, categorization,
Representation learning
BibRef
Yang, Z.Z.[Zi-Zheng],
Jin, X.[Xin],
Zheng, K.[Kecheng],
Zhao, F.[Feng],
Unleashing Potential of Unsupervised Pre-Training with Intra-Identity
Regularization for Person Re-Identification,
CVPR22(14278-14287)
IEEE DOI
2210
Representation learning, Pipelines, Self-supervised learning,
Robustness, Pattern recognition, Task analysis,
Self- semi- meta- unsupervised learning
BibRef
Wang, Y.Q.[Ying-Quan],
Zhang, P.P.[Ping-Ping],
Gao, S.[Shang],
Geng, X.[Xia],
Lu, H.[Hu],
Wang, D.[Dong],
Pyramid Spatial-Temporal Aggregation for Video-based Person
Re-Identification,
ICCV21(12006-12015)
IEEE DOI
2203
Mars, Correlation, Codes, Fuses, Aggregates, Interference,
Image and video retrieval,
BibRef
Chen, X.D.[Xiao-Dong],
Liu, X.C.[Xin-Chen],
Liu, W.[Wu],
Zhang, X.P.[Xiao-Ping],
Zhang, Y.D.[Yong-Dong],
Mei, T.[Tao],
Explainable Person Re-Identification with Attribute-guided Metric
Distillation,
ICCV21(11793-11802)
IEEE DOI
2203
Measurement, Visualization, Semantics, Image retrieval,
Convolutional neural networks, Task analysis, Explainable AI
BibRef
Rao, Y.M.[Yong-Ming],
Chen, G.Y.[Guang-Yi],
Lu, J.W.[Ji-Wen],
Zhou, J.[Jie],
Counterfactual Attention Learning for Fine-Grained Visual
Categorization and Re-identification,
ICCV21(1005-1014)
IEEE DOI
2203
Learning systems, Training, Visualization, Image recognition, Costs,
Computational modeling, Recognition and classification,
BibRef
He, T.Y.[Tian-Yu],
Jin, X.[Xin],
Shen, X.[Xu],
Huang, J.Q.[Jian-Qiang],
Chen, Z.B.[Zhi-Bo],
Hua, X.S.[Xian-Sheng],
Dense Interaction Learning for Video-based Person Re-identification,
ICCV21(1470-1481)
IEEE DOI
2203
Architecture, Buildings, Feature extraction,
Decoding, Task analysis, Video analysis and understanding,
Vision applications and systems
BibRef
Ji, H.X.[Hao-Xuanye],
Wang, L.[Le],
Zhou, S.P.[San-Ping],
Tang, W.[Wei],
Zheng, N.N.[Nan-Ning],
Hua, G.[Gang],
Meta Pairwise Relationship Distillation for Unsupervised Person
Re-identification,
ICCV21(3641-3650)
IEEE DOI
2203
Training, Representation learning, Visualization,
Image color analysis, Estimation, Feature extraction,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Zheng, Y.[Yi],
Tang, S.X.[Shi-Xiang],
Teng, G.L.[Guo-Long],
Ge, Y.X.[Yi-Xiao],
Liu, K.J.[Kai-Jian],
Qin, J.[Jing],
Qi, D.L.[Dong-Lian],
Chen, D.P.[Da-Peng],
Online Pseudo Label Generation by Hierarchical Cluster Dynamics for
Adaptive Person Re-identification,
ICCV21(8351-8361)
IEEE DOI
2203
Training, Adaptation models, Heuristic algorithms,
Computational modeling, Clustering methods, Semantics, Representation learning
BibRef
Isobe, T.[Takashi],
Li, D.[Dong],
Tian, L.[Lu],
Chen, W.H.[Wei-Hua],
Shan, Y.[Yi],
Wang, S.J.[Sheng-Jin],
Towards Discriminative Representation Learning for Unsupervised
Person Re-identification,
ICCV21(8506-8516)
IEEE DOI
2203
Representation learning, Training, Target recognition,
Handheld computers, Pipelines, Clustering algorithms, Biometrics
BibRef
Haghighi, A.B.[Amir Bitaraf],
Taheri, M.[Mohammad],
Person Re-Identification using Ensemble of Networks on Pose
Transferred Images,
IPRIA21(1-5)
IEEE DOI
2201
Measurement, Visualization, Image recognition, Image analysis,
Neural networks, Feature extraction, Video surveillance,
Ensemble Learning
BibRef
Sun, Z.Z.[Zong-Zhe],
Zhao, F.[Feng],
Wu, F.[Feng],
Unsupervised Person Re-Identification Via Global-Level and
Patch-Level Discriminative Feature Learning,
ICIP21(2363-2367)
IEEE DOI
2201
Image processing, Benchmark testing, Data models,
Person re-identification, unsupervised learning, domain adaptation
BibRef
Sun, W.Y.[Wen-Yu],
Xie, J.Y.[Ji-Yang],
Qiu, J.Y.[Jia-Yan],
Ma, Z.Y.[Zhan-Yu],
Part Uncertainty Estimation Convolutional Neural Network for Person
Re-Identification,
ICIP21(2304-2308)
IEEE DOI
2201
Training, Uncertainty, Filtering, Image processing, Estimation,
Robustness, Data models, Person ReID, uncertainty estimation,
quality filter
BibRef
Cheng, Y.Z.[Yun-Zhou],
Xiao, G.Q.[Guo-Qiang],
Tang, X.Q.[Xiao-Qin],
Ma, W.Z.[Wen-Zhuo],
Gou, X.Y.[Xin-Ye],
Two-Phase Feature Fusion Network for Visible-Infrared Person
Re-Identification,
ICIP21(1149-1153)
IEEE DOI
2201
Fuses, Convolution, Image processing, Cameras, Mutual information,
Person re-identification, cross-modality, feature fusion, deep supervision
BibRef
Zhang, Z.Y.[Zi-Yue],
Jiang, S.[Shuai],
Huang, C.Z.T.[Cong-Zhen-Tao],
Xu, R.Y.D.[Richard Yi Da],
Resolution-Invariant Person ReId Based on Feature Transformation and
Self-Weighted Attention,
ICIP21(1134-1138)
IEEE DOI
2201
Image resolution, Video sequences, Transforms, Benchmark testing,
Cameras, Person re-identification, resolution adaptive,
self-weighted attention
BibRef
Tang, Q.[Qing],
Jo, K.H.[Kang-Hyun],
Unsupervised Person Re-Identification Via Nearest Neighbor
Collaborative Training Strategy,
ICIP21(1139-1143)
IEEE DOI
2201
Training, Annotations, Image processing, Collaboration,
Artificial neural networks, Noise measurement,
pseudo label refinery
BibRef
Herzog, F.[Fabian],
Ji, X.[Xunbo],
Teepe, T.[Torben],
Hörmann, S.[Stefan],
Gilg, J.[Johannes],
Rigoll, G.[Gerhard],
Lightweight Multi-Branch Network for Person Re-Identification,
ICIP21(1129-1133)
IEEE DOI
2201
Training, Schedules, Surveillance, Neural networks,
Deep architecture, Cameras, Feature extraction, Image Processing
BibRef
Lusardi, C.[Christian],
Taufique, A.M.N.[Abu Md Niamul],
Savakis, A.[Andreas],
Robust Multi-Object Tracking Using Re-Identification Features and
Graph Convolutional Networks,
WAAMI21(3861-3870)
IEEE DOI
2112
Training, Benchmark testing,
Feature extraction, Robustness, Graph neural networks
BibRef
Fu, D.P.[Deng-Pan],
Chen, D.D.[Dong-Dong],
Bao, J.M.[Jian-Min],
Yang, H.[Hao],
Yuan, L.[Lu],
Zhang, L.[Lei],
Li, H.Q.[Hou-Qiang],
Chen, D.[Dong],
Unsupervised Pre-training for Person Re-identification,
CVPR21(14745-14754)
IEEE DOI
2111
Annotations, Computational modeling, Cameras,
Data models, Pattern recognition, Videos
BibRef
Dai, Y.X.[Yong-Xing],
Li, X.T.[Xiao-Tong],
Liu, J.[Jun],
Tong, Z.[Zekun],
Duan, L.Y.[Ling-Yu],
Generalizable Person Re-identification with Relevance-aware Mixture
of Experts,
CVPR21(16140-16149)
IEEE DOI
2111
Training, Adaptation models, Pipelines,
Decorrelation, Pattern recognition, Testing
BibRef
Liu, X.[Xuehu],
Zhang, P.P.[Ping-Ping],
Yu, C.Y.[Chen-Yang],
Lu, H.C.[Hu-Chuan],
Yang, X.Y.[Xiao-Yun],
Watching You: Global-guided Reciprocal Learning for Video-based
Person Re-identification,
CVPR21(13329-13338)
IEEE DOI
2111
Correlation, Codes, Video sequences, Semantics,
Estimation, Benchmark testing
BibRef
Zhang, Z.[Zhong],
Zhang, H.[Haijia],
Liu, S.[Shuang],
Person Re-identification using Heterogeneous Local Graph Attention
Networks,
CVPR21(12131-12140)
IEEE DOI
2111
Aggregates, Pattern recognition, Context modeling
BibRef
Zhang, T.Y.[Tian-Yu],
Xie, L.X.[Ling-Xi],
Wei, L.[Longhui],
Zhuang, Z.J.[Zi-Jie],
Zhang, Y.F.[Yong-Fei],
Li, B.[Bo],
Tian, Q.[Qi],
UnrealPerson:
An Adaptive Pipeline towards Costless Person Re-identification,
CVPR21(11501-11510)
IEEE DOI
2111
Training, Costs, Annotations, Image synthesis,
Data integrity, Pipelines
BibRef
Li, H.J.[Han-Jun],
Wu, G.[Gaojie],
Zheng, W.S.[Wei-Shi],
Combined Depth Space based Architecture Search For Person
Re-identification,
CVPR21(6725-6734)
IEEE DOI
2111
Training,
Network architecture, Search problems, Feature extraction, Neck
BibRef
Chen, H.[Hao],
Wang, Y.[Yaohui],
Lagadec, B.[Benoit],
Dantcheva, A.[Antitza],
Bremond, F.[Francois],
Joint Generative and Contrastive Learning for Unsupervised Person
Re-identification,
CVPR21(2004-2013)
IEEE DOI
2111
Training, Adaptation models,
Codes, Image synthesis, Generative adversarial networks
BibRef
Bai, Y.[Yan],
Jiao, J.[Jile],
Ce, W.[Wang],
Liu, J.[Jun],
Lou, Y.H.[Yi-Hang],
Feng, X.T.[Xue-Tao],
Duan, L.Y.[Ling-Yu],
Person30K: A Dual-Meta Generalization Network for Person
Re-Identification,
CVPR21(2123-2132)
IEEE DOI
2111
Training, Computational modeling,
Benchmark testing, Extraterrestrial measurements, Cameras, Data models
BibRef
Chen, Y.[Yehansen],
Wan, L.[Lin],
Li, Z.H.[Zhi-Hang],
Jing, Q.Y.[Qian-Yan],
Sun, Z.Y.[Zong-Yuan],
Neural Feature Search for RGB-Infrared Person Re-Identification,
CVPR21(587-597)
IEEE DOI
2111
Manuals, Benchmark testing, Performance gain,
Feature extraction, Search problems, Pattern recognition
BibRef
Chen, H.[Hao],
Lagadec, B.[Benoit],
Brémond, F.[François],
Enhancing Diversity in Teacher-Student Networks via Asymmetric
branches for Unsupervised Person Re-identification,
WACV21(1-10)
IEEE DOI
2106
Training, Knowledge engineering, Couplings,
Annotations, Neural networks
BibRef
Quispe, R.[Rodolfo],
Pedrini, H.[Helio],
Top-DB-Net: Top DropBlock for Activation Enhancement in Person
Re-Identification,
ICPR21(2980-2987)
IEEE DOI
2105
Focusing, Streaming media, Cameras, Pattern recognition, Reliability,
Task analysis, Testing
BibRef
Munir, A.[Asad],
Martinel, N.[Niki],
Micheloni, C.[Christian],
Self and Channel Attention Network for Person Re-Identification,
ICPR21(4025-4031)
IEEE DOI
2105
Training, Measurement, Correlation, Focusing, Benchmark testing,
Market research, Pattern recognition
BibRef
Li, Z.[Zhen],
Shao, H.Y.[Han-Yang],
Niu, L.[Liang],
Xue, N.[Nian],
Progressive Learning Algorithm for Efficient Person
Re-Identification,
ICPR21(16-23)
IEEE DOI
2105
Computational modeling, Memory management, Buildings,
Programmable logic arrays, Market research, Inference algorithms,
Computational efficiency
BibRef
Hao, G.[Gehan],
Yang, Y.[Yang],
Zhou, X.[Xue],
Wang, G.[Guanan],
Lei, Z.[Zhen],
Horizontal Flipping Assisted Disentangled Feature Learning for
Semi-supervised Person Re-identification,
ACCV20(III:21-37).
Springer DOI
2103
BibRef
Tang, Z.M.[Zeng-Ming],
Huang, J.[Jun],
Branch Interaction Network for Person Re-identification,
ACCV20(III:322-337).
Springer DOI
2103
BibRef
Wang, L.[Li],
Fan, B.Y.[Bao-Yu],
Guo, Z.H.[Zhen-Hua],
Zhao, Y.Q.[Ya-Qian],
Zhang, R.Z.[Run-Ze],
Li, R.G.[Ren-Gang],
Gong, W.F.[Wei-Feng],
Dense-scale Feature Learning in Person Re-identification,
ACCV20(VI:341-357).
Springer DOI
2103
BibRef
Wang, Z.D.[Zhong-Dao],
Zhang, J.W.[Jing-Wei],
Zheng, L.[Liang],
Liu, Y.X.[Yi-Xuan],
Sun, Y.F.[Yi-Fan],
Li, Y.[Yali],
Wang, S.J.[Sheng-Jin],
CycAs:
Self-supervised Cycle Association for Learning Re-identifiable Descriptions,
ECCV20(XI:72-88).
Springer DOI
2011
BibRef
Zhang, Y.,
Shi, W.,
Liu, S.,
Bao, J.,
Wei, Y.,
Scale-Invariant Siamese Network For Person Re-Identification,
ICIP20(2436-2440)
IEEE DOI
2011
Visualization, Training, Silicon, Feeds,
Feature extraction, Tensile stress, Scale-invariant features,
Person re-identification
BibRef
Munir, A.,
Martinel, N.,
Micheloni, C.,
Multi Branch Siamese Network For Person Re-Identification,
ICIP20(2351-2355)
IEEE DOI
2011
Cameras, Training, Robustness, Benchmark testing,
Entropy, Person Re-Identification, Cycle-GAN
BibRef
Liu, C.T.[Chih-Ting],
Chen, J.C.[Jun-Cheng],
Chen, C.S.[Chu-Song],
Chien, S.Y.[Shao-Yi],
Video-based Person Re-identification without Bells and Whistles,
AMFG21(1491-1500)
IEEE DOI
2109
Protocols, Computational modeling, Lighting, Cameras, Data models
BibRef
Wu, C.W.,
Liu, C.T.,
Tu, W.C.,
Tsao, Y.,
Wang, Y.C.F.,
Chien, S.Y.,
Space-Time Guided Association Learning For Unsupervised Person
Re-Identification,
ICIP20(2261-2265)
IEEE DOI
2011
Feature extraction, Cameras, Training, Robustness,
Prediction algorithms, Labeling, Visualization
BibRef
Ji, Z.L.[Zi-Long],
Zou, X.L.[Xiao-Long],
Lin, X.O.[Xia-Ohan],
Liu, X.[Xiao],
Huang, T.J.[Tie-Jun],
Wu, S.[Si],
An Attention-driven Two-stage Clustering Method for Unsupervised Person
Re-identification,
ECCV20(XXVIII:20-36).
Springer DOI
2011
BibRef
Yuan, Y.,
Chen, W.,
Yang, Y.,
Wang, Z.,
In Defense of the Triplet Loss Again: Learning Robust Person
Re-Identification with Fast Approximated Triplet Loss and Label
Distillation,
WiCV20(1454-1463)
IEEE DOI
2008
Fats, Noise measurement, Training, Robustness, Data models,
Upper bound, Complexity theory
BibRef
Fan, L.,
Li, T.,
Fang, R.,
Hristov, R.,
Yuan, Y.,
Katabi, D.,
Learning Longterm Representations for Person Re-Identification Using
Radio Signals,
CVPR20(10696-10706)
IEEE DOI
2008
Feature extraction, Radio frequency, RF signals, Heating systems,
Videos, Cameras, Lighting
BibRef
Chen, X.,
Fu, C.,
Zhao, Y.,
Zheng, F.,
Song, J.,
Ji, R.,
Yang, Y.,
Salience-Guided Cascaded Suppression Network for Person
Re-Identification,
CVPR20(3297-3307)
IEEE DOI
2008
Feature extraction, Semantics, Aggregates, Training, Testing,
Task analysis, Biological system modeling
BibRef
Avola, D.[Danilo],
Cascio, M.[Marco],
Cinque, L.[Luigi],
Fagioli, A.[Alessio],
Foresti, G.L.[Gian Luca],
Massaroni, C.[Cristiano],
Master and Rookie Networks for Person Re-identification,
CAIP19(II:470-479).
Springer DOI
1909
BibRef
Matiyali, N.,
Sharma, G.,
Video Person Re-Identification using Learned Clip Similarity
Aggregation,
WACV20(2644-2653)
IEEE DOI
2006
Task analysis, Video sequences, Feature extraction,
Benchmark testing, Measurement, Optical imaging
BibRef
Chen, H.,
Lagadec, B.,
Bremond, F.,
Learning Discriminative and Generalizable Representations by
Spatial-Channel Partition for Person Re-Identification,
WACV20(2472-2481)
IEEE DOI
2006
Feature extraction, Task analysis, Robustness, Semantics,
Neural networks, Cameras, Training
BibRef
Chen, G.,
Lin, C.,
Ren, L.,
Lu, J.,
Zhou, J.,
Self-Critical Attention Learning for Person Re-Identification,
ICCV19(9636-9645)
IEEE DOI
2004
image recognition, learning (artificial intelligence),
person re-identification, Learning (artificial intelligence)
BibRef
Chen, T.,
Ding, S.,
Xie, J.,
Yuan, Y.,
Chen, W.,
Yang, Y.,
Ren, Z.,
Wang, Z.,
ABD-Net: Attentive but Diverse Person Re-Identification,
ICCV19(8350-8360)
IEEE DOI
2004
feature extraction, learning (artificial intelligence),
ABD-Net seamlessly, diversity regularizations, Euclidean distance
BibRef
Wu, J.,
Liu, H.,
Yang, Y.,
Lei, Z.,
Liao, S.,
Li, S.,
Unsupervised Graph Association for Person Re-Identification,
ICCV19(8320-8329)
IEEE DOI
2004
cameras, graph theory, image motion analysis,
image recognition, image representation, object detection, Machine learning
BibRef
Wu, A.,
Zheng, W.,
Lai, J.,
Unsupervised Person Re-Identification by Camera-Aware Similarity
Consistency Learning,
ICCV19(6921-6930)
IEEE DOI
2004
cameras, image matching, object detection, statistical analysis,
supervised learning, unsupervised learning, video surveillance, Lighting
BibRef
Bryan, B.,
Gong, Y.,
Zhang, Y.,
Poellabauer, C.,
Second-Order Non-Local Attention Networks for Person
Re-Identification,
ICCV19(3759-3768)
IEEE DOI
2004
image representation, learning (artificial intelligence),
neural nets, statistics, dropout mechanism, consecutive regions,
Computer architecture
BibRef
Chen, B.,
Deng, W.,
Hu, J.,
Mixed High-Order Attention Network for Person Re-Identification,
ICCV19(371-381)
IEEE DOI
2004
Code, Re-Identification.
WWW Link. image processing, learning (artificial intelligence), statistics,
mixed high-order attention network, person re-identification, Cameras
BibRef
Hou, R.B.[Rui-Bing],
Ma, B.P.[Bing-Peng],
Chang, H.[Hong],
Gu, X.Q.[Xin-Qian],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Interaction-And-Aggregation Network for Person Re-Identification,
CVPR19(9309-9318).
IEEE DOI
2002
BibRef
Meng, J.[Jingke],
Wu, S.[Sheng],
Zheng, W.S.[Wei-Shi],
Weakly Supervised Person Re-Identification,
CVPR19(760-769).
IEEE DOI
2002
BibRef
Yang, W.J.[Wen-Jie],
Huang, H.J.[Hou-Jing],
Zhang, Z.[Zhang],
Chen, X.T.[Xiao-Tang],
Huang, K.Q.[Kai-Qi],
Zhang, S.[Shu],
Towards Rich Feature Discovery With Class Activation Maps Augmentation
for Person Re-Identification,
CVPR19(1389-1398).
IEEE DOI
2002
BibRef
Zheng, Z.D.[Zhe-Dong],
Yang, X.D.[Xiao-Dong],
Yu, Z.[Zhiding],
Zheng, L.[Liang],
Yang, Y.[Yi],
Kautz, J.[Jan],
Joint Discriminative and Generative Learning for Person
Re-Identification,
CVPR19(2133-2142).
IEEE DOI
2002
BibRef
Yu, H.X.[Hong-Xing],
Zheng, W.S.[Wei-Shi],
Wu, A.[Ancong],
Guo, X.W.[Xiao-Wei],
Gong, S.G.[Shao-Gang],
Lai, J.H.[Jian-Huang],
Unsupervised Person Re-Identification by Soft Multilabel Learning,
CVPR19(2143-2152).
IEEE DOI
2002
BibRef
Yang, Q.Z.[Qi-Ze],
Yu, H.X.[Hong-Xing],
Wu, A.[Ancong],
Zheng, W.S.[Wei-Shi],
Patch-Based Discriminative Feature Learning for Unsupervised Person
Re-Identification,
CVPR19(3628-3637).
IEEE DOI
2002
BibRef
Zhao, Y.[Yiru],
Shen, X.[Xu],
Jin, Z.M.[Zhong-Ming],
Lu, H.T.[Hong-Tao],
Hua, X.S.[Xian-Sheng],
Attribute-Driven Feature Disentangling and Temporal Aggregation for
Video Person Re-Identification,
CVPR19(4908-4917).
IEEE DOI
2002
BibRef
Zheng, M.[Meng],
Karanam, S.[Srikrishna],
Wu, Z.Y.[Zi-Yan],
Radke, R.J.[Richard J.],
Re-Identification With Consistent Attentive Siamese Networks,
CVPR19(5728-5737).
IEEE DOI
2002
BibRef
Sun, Y.F.[Yi-Fan],
Xu, Q.[Qin],
Li, Y.[Yali],
Zhang, C.[Chi],
Li, Y.K.[Yi-Kang],
Wang, S.J.[Sheng-Jin],
Sun, J.[Jian],
Perceive Where to Focus: Learning Visibility-Aware Part-Level Features
for Partial Person Re-Identification,
CVPR19(393-402).
IEEE DOI
2002
BibRef
Tay, C.P.[Chiat-Pin],
Roy, S.[Sharmili],
Yap, K.H.[Kim-Hui],
AANet: Attribute Attention Network for Person Re-Identifications,
CVPR19(7127-7136).
IEEE DOI
2002
BibRef
Loesch, A.,
Rabarisoa, J.,
Audigier, R.,
End-To-End Person Search Sequentially Trained On Aggregated Dataset,
ICIP19(4574-4578)
IEEE DOI
1910
Re-identification, person detection, person search,
multi-task learning, cross-dataset
BibRef
Sun, L.,
Liu, J.,
Zhu, Y.,
Jiang, Z.,
Local to Global with Multi-Scale Attention Network for Person
Re-Identification,
ICIP19(2254-2258)
IEEE DOI
1910
Person re-identification, local information, global information, spatial attention
BibRef
Wu, G.,
Zhu, X.,
Gong, S.,
Person Re-Identification by Ranking Ensemble Representations,
ICIP19(2259-2263)
IEEE DOI
1910
Person re-identification, ranking list
BibRef
Guo, H.,
Wu, H.,
Zhao, C.,
Zhang, H.,
Wang, J.,
Lu, H.,
Cascade Attention Network for Person Re-Identification,
ICIP19(2264-2268)
IEEE DOI
1910
cascade attention network, human parsing,
spatial-channel attention module, person re-identification
BibRef
Liu, S.,
Qi, L.,
Zhang, Y.,
Shi, W.,
Dual Reverse Attention Networks for Person Re-Identification,
ICIP19(1232-1236)
IEEE DOI
1910
Person re-identification, hard examples, dual reverse attention networks
BibRef
Fan, X.[Xing],
Luo, H.[Hao],
Zhang, X.[Xuan],
He, L.X.[Ling-Xiao],
Zhang, C.[Chi],
Jiang, W.[Wei],
SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and
Partial Person Re-identification,
ACCV18(II:19-34).
Springer DOI
1906
BibRef
Hara, K.[Kensho],
Kataoka, H.[Hirokatsu],
Inaba, M.[Masaki],
Narioka, K.[Kenichi],
Satoh, Y.[Yutaka],
Recognizing People in Blind Spots Based on Surrounding Behavior,
PersonContext18(II:562-570).
Springer DOI
1905
BibRef
Zhu, X.R.[Xie-Rong],
Liu, J.W.[Jia-Wei],
Xie, H.T.[Hong-Tao],
Zha, Z.J.[Zheng-Jun],
Adaptive Alignment Network for Person Re-identification,
MMMod19(II:16-27).
Springer DOI
1901
BibRef
Tian, M.Q.[Mao-Qing],
Yi, S.A.[Shu-Ai],
Li, H.S.[Hong-Sheng],
Li, S.H.[Shi-Hua],
Zhang, X.S.[Xue-Sen],
Shi, J.P.[Jian-Ping],
Yan, J.J.[Jun-Jie],
Wang, X.G.[Xiao-Gang],
Eliminating Background-bias for Robust Person Re-identification,
CVPR18(5794-5803)
IEEE DOI
1812
Testing, Training, Neural networks, Visualization, Cameras, Probes
BibRef
Jiang, N.,
Liu, J.,
Sun, C.,
Wang, Y.,
Zhou, Z.,
Wu, W.,
Orientation-Guided Similarity Learning for Person Re-identification,
ICPR18(2056-2061)
IEEE DOI
1812
Feature extraction, Training, Measurement, Shoulder, Pose estimation,
Image color analysis
BibRef
Huang, X.,
Xu, J.,
Guo, G.,
Incremental Kernel Null Foley-Sammon Transform for Person
Re-identification,
ICPR18(1683-1688)
IEEE DOI
1812
Transforms, Data models, Null space, Learning systems, Training, Measurement
BibRef
Guo, R.,
Li, C.,
Li, Y.,
Lin, J.,
Density-Adaptive Kernel based Re-Ranking for Person Re-Identification,
ICPR18(982-987)
IEEE DOI
1812
Kernel, Probes, Task analysis, Proposals, Surveillance, Cameras,
Benchmark testing
BibRef
Lv, J.,
Chen, W.,
Li, Q.,
Yang, C.,
Unsupervised Cross-Dataset Person Re-identification by Transfer
Learning of Spatial-Temporal Patterns,
CVPR18(7948-7956)
IEEE DOI
1812
Visualization, Silicon, Cameras, Surveillance, Supervised learning,
Feature extraction, Optimization
BibRef
Roy, S.,
Paul, S.,
Young, N.E.,
Roy-Chowdhury, A.K.,
Exploiting Transitivity for Learning Person Re-identification Models
on a Budget,
CVPR18(7064-7072)
IEEE DOI
1812
Cameras, Labeling, Measurement, Optimization, Manuals, Task analysis,
Image edge detection
BibRef
Wu, Y.[Yu],
Lin, Y.T.[Yu-Tian],
Dong, X.Y.[Xuan-Yi],
Yan, Y.[Yan],
Ouyang, W.L.[Wan-Li],
Yang, Y.[Yi],
Exploit the Unknown Gradually: One-Shot Video-Based Person
Re-identification by Stepwise Learning,
CVPR18(5177-5186)
IEEE DOI
1812
Training, Reliability, Data models, Estimation, Feature extraction,
Task analysis, Cameras
BibRef
Chang, X.,
Hospedales, T.M.,
Xiang, T.,
Multi-level Factorisation Net for Person Re-identification,
CVPR18(2109-2118)
IEEE DOI
1812
Semantics, Visualization,
Feature extraction, Frequency modulation, Task analysis, Cameras
BibRef
Xu, J.,
Zhao, R.,
Zhu, F.,
Wang, H.,
Ouyang, W.,
Attention-Aware Compositional Network for Person Re-identification,
CVPR18(2119-2128)
IEEE DOI
1812
For important reasons, the dataset used for this work has been removed.
Feature extraction, Clutter, Pose estimation, Legged locomotion,
Cameras, Visualization, Task analysis
BibRef
Li, W.,
Zhu, X.,
Gong, S.,
Harmonious Attention Network for Person Re-identification,
CVPR18(2285-2294)
IEEE DOI
1812
Data models, Computational modeling, Visualization, Training,
Surveillance, Training data
BibRef
Shi, X.,
Shan, S.,
Kan, M.,
Wu, S.,
Chen, X.,
Real-Time Rotation-Invariant Face Detection with Progressive
Calibration Networks,
CVPR18(2295-2303)
IEEE DOI
1812
Face, Detectors, Calibration, Face detection, Training,
Task analysis, Real-time systems
BibRef
Zhong, Z.[Zhun],
Zheng, L.[Liang],
Li, S.Z.[Shao-Zi],
Yang, Y.[Yi],
Generalizing a Person Retrieval Model Hetero- and Homogeneously,
ECCV18(XIII: 176-192).
Springer DOI
1810
BibRef
Zhang, X.,
Bhanu, B.,
An Unbiased Temporal Representation for Video-Based Person
Re-Identification,
ICIP18(838-842)
IEEE DOI
1809
Training, Feature extraction, Cameras, Recurrent neural networks,
Task analysis, Euclidean distance,
recurrent neural networks (RNNs)
BibRef
Martinez, J.,
Black, M.J.,
Romero, J.,
On Human Motion Prediction Using Recurrent Neural Networks,
CVPR17(4674-4683)
IEEE DOI
1711
Hidden Markov models, Mathematical model, Predictive models,
Recurrent neural networks, Training, Visualization
BibRef
Ji, X.L.[Xiang-Li],
Luo, G.B.[Gui-Bo],
Zhu, Y.S.[Yue-Sheng],
A New Temporal Deconvolutional Pyramid Network for Action Detection,
ACCV18(IV:696-711).
Springer DOI
1906
BibRef
Mumtaz, S.,
Mubariz, N.,
Saleem, S.,
Fraz, M.M.,
Weighted hybrid features for person re-identification,
IPTA17(1-6)
IEEE DOI
1804
cameras, feature extraction, learning (artificial intelligence),
pose estimation, video surveillance, LOMO features,
Person Re-identification
BibRef
Sun, L.,
Zhou, Y.,
Jiang, Z.,
Men, A.,
Coupled analysis-synthesis dictionary learning for person
re-identification,
ICIP17(365-369)
IEEE DOI
1803
Cameras, Dictionaries, Encoding, Machine learning, Optimization,
Probes, Training, LFDA, Person re-identification,
coupled dictionary learning
BibRef
Xu, W.,
Chi, H.,
Zhou, L.,
Huang, X.,
Yang, J.,
Self-paced least square semi-coupled dictionary learning for person
re-identification,
ICIP17(3705-3709)
IEEE DOI
1803
Dictionaries, Linear programming, Machine learning, Measurement,
Optimization, Probes, Support vector machines, Self-Paced Learning,
samplespecific SVM
BibRef
Zhong, W.,
Xiong, H.,
Yang, Z.,
Zhang, T.,
Bi-directional long short-term memory architecture for person
re-identification with modified triplet embedding,
ICIP17(1562-1566)
IEEE DOI
1803
Indexes, Long-Short Term Memory,
bi-directional information flow, modified triplet, spatial correlation
BibRef
Xu, S.,
Cheng, Y.,
Gu, K.,
Yang, Y.,
Chang, S.,
Zhou, P.,
Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based
Person Re-identification,
ICCV17(4743-4752)
IEEE DOI
1802
feature extraction, image matching, image representation,
image sequences, video signal processing, video surveillance,
Visualization
BibRef
Zhou, Z.,
Huang, Y.,
Wang, W.,
Wang, L.,
Tan, T.,
See the Forest for the Trees: Joint Spatial and Temporal Recurrent
Neural Networks for Video-Based Person Re-identification,
CVPR17(6776-6785)
IEEE DOI
1711
Feature extraction,
Image sequences, Measurement, Recurrent, neural, networks
BibRef
Zhang, Y.,
Li, B.,
Lu, H.,
Irie, A.,
Ruan, X.,
Sample-Specific SVM Learning for Person Re-identification,
CVPR16(1278-1287)
IEEE DOI
1612
BibRef
Peng, P.X.[Pei-Xi],
Tian, Y.H.[Yong-Hong],
Xiang, T.[Tao],
Wang, Y.W.[Yao-Wei],
Huang, T.J.[Tie-Jun],
Joint Learning of Semantic and Latent Attributes,
ECCV16(IV: 336-353).
Springer DOI
1611
Some attributes are discriminative, some not.
BibRef
Varior, R.R.[Rahul Rama],
Shuai, B.[Bing],
Lu, J.W.[Ji-Wen],
Xu, D.[Dong],
Wang, G.[Gang],
A Siamese Long Short-Term Memory Architecture for Human
Re-identification,
ECCV16(VII: 135-153).
Springer DOI
1611
BibRef
Wang, W.,
Taalimi, A.,
Duan, K.,
Guo, R.,
Qi, H.,
Learning patch-dependent kernel forest for person re-identification,
WACV16(1-9)
IEEE DOI
1606
Cameras
BibRef
Zhou, Q.[Qin],
Zheng, S.[Shibao],
Su, H.[Hang],
Yang, H.[Hua],
Wang, Y.[Yu],
Wu, S.[Shuang],
Kernelized View Adaptive Subspace Learning for Person Re-identification,
BMVC15(xx-yy).
DOI Link
1601
BibRef
Kodirov, E.[Elyor],
Xiang, T.[Tao],
Gong, S.G.[Shao-Gang],
Dictionary Learning with Iterative Laplacian Regularisation for
Unsupervised Person Re-identification,
BMVC15(xx-yy).
DOI Link
1601
See also Unsupervised Domain Adaptation for Zero-Shot Learning.
BibRef
Roth, J.[Joseph],
Liu, X.M.[Xiao-Ming],
On the Exploration of Joint Attribute Learning for Person
Re-identification,
ACCV14(I: 673-688).
Springer DOI
1504
BibRef
Wang, H.X.[Han-Xiao],
Gong, S.G.[Shao-Gang],
Xiang, T.[Tao],
Unsupervised Learning of Generative Topic Saliency for Person
Re-identification,
BMVC14(xx-yy).
HTML Version.
1410
BibRef
Zhao, Y.[Yanna],
Wang, L.[Lei],
Liu, Y.C.[Yun-Cai],
Set-Based Feature Learning for Person Re-identification via
Third-Party Images,
ACPR13(401-404)
IEEE DOI
1408
feature extraction
BibRef
Xu, Y.L.[Yuan-Lu],
Zhou, H.F.[Hong-Fei],
Wang, Q.[Qing],
Lin, L.[Liang],
Realtime object-of-interest tracking by learning Composite Patch-based
Templates,
ICIP12(389-392).
IEEE DOI
1302
BibRef
Wu, Y.[Yang],
Li, W.[Wei],
Minoh, M.[Michihiko],
Mukunoki, M.[Masayuki],
Can feature-based inductive transfer learning help person
re-identification?,
ICIP13(2812-2816)
IEEE DOI
1402
Person re-identification
BibRef
Brand, Y.[Yulia],
Avraham, T.[Tamar],
Lindenbaum, M.[Michael],
Transitive Re-identification,
BMVC13(xx-yy).
DOI Link
1402
BibRef
Avraham, T.[Tamar],
Gurvich, I.[Ilya],
Lindenbaum, M.[Michael],
Markovitch, S.[Shaul],
Learning Implicit Transfer for Person Re-identification,
Re-Id12(I: 381-390).
Springer DOI
1210
BibRef
Goldhammer, M.[Michael],
Doll, K.[Konrad],
Brunsmann, U.[Ulrich],
Gensler, A.[Andre],
Sick, B.[Bernhard],
Pedestrian's Trajectory Forecast in Public Traffic with Artificial
Neural Networks,
ICPR14(4110-4115)
IEEE DOI
1412
Head
BibRef
Nickel, K.[Kai],
Stiefelhagen, R.[Rainer],
Dynamic Integration of Generalized Cues for Person Tracking,
ECCV08(IV: 514-526).
Springer DOI
0810
BibRef
Bauml, M.[Martin],
Stiefelhagen, R.[Rainer],
Evaluation of local features for person re-identification in image
sequences,
AVSBS11(291-296).
IEEE DOI
1111
BibRef
And:
Interactive person-retrieval in a distributed camera network,
AVSBS11(525-526).
IEEE DOI
1111
AVSS 2011 demo session.
BibRef
Hu, L.[Lei],
Wang, Y.Z.[Yi-Zhou],
Jiang, S.Q.[Shu-Qiang],
Huang, Q.M.[Qing-Ming],
Gao, W.[Wen],
Human reappearance detection based on on-line learning,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Metric Learning, Re-Identification Issues .