Borgia, A.,
Hua, Y.,
Kodirov, E.,
Robertson, N.M.[Neil M.],
Cross-View Discriminative Feature Learning for Person
Re-Identification,
IP(27), No. 11, November 2018, pp. 5338-5349.
IEEE DOI
1809
feature extraction, image representation,
learning (artificial intelligence),
discriminative features
BibRef
Borgia, A.[Alessandro],
Hua, Y.[Yang],
Kodirov, E.[Elyor],
Robertson, N.M.[Neil M.],
GAN-Based Pose-Aware Regulation for Video-Based Person
Re-Identification,
WACV19(1175-1184)
IEEE DOI
1904
gait analysis, image matching, image sequences, pose estimation,
recurrent neural nets, inter-sequence temporal dependencies,
Measurement
BibRef
Lin, C.Z.[Chun-Ze],
Lu, J.W.[Ji-Wen],
Zhou, J.[Jie],
Multi-Grained Deep Feature Learning for Robust Pedestrian Detection,
CirSysVideo(29), No. 12, December 2019, pp. 3608-3621.
IEEE DOI
1912
Feature extraction, Detectors, Image resolution, Semantics,
Proposals, Task analysis, Generative adversarial networks,
deep feature learning
BibRef
Lin, C.Z.[Chun-Ze],
Lu, J.W.[Ji-Wen],
Wang, G.[Gang],
Zhou, J.[Jie],
Graininess-Aware Deep Feature Learning for Robust Pedestrian
Detection,
IP(29), 2020, pp. 3820-3834.
IEEE DOI
2002
BibRef
Earlier:
Graininess-Aware Deep Feature Learning for Pedestrian Detection,
ECCV18(IX: 745-761).
Springer DOI
1810
Pedestrian detection, attention, deep learning, graininess
BibRef
Chen, G.Y.[Guang-Yi],
Lu, J.W.[Ji-Wen],
Yang, M.[Ming],
Zhou, J.[Jie],
Spatial-Temporal Attention-Aware Learning for Video-Based Person
Re-Identification,
IP(28), No. 9, Sep. 2019, pp. 4192-4205.
IEEE DOI
1908
feature extraction, image matching, image representation,
image sequences, learning (artificial intelligence),
spatial-temporal attention model
BibRef
Chen, G.Y.[Guang-Yi],
Lu, J.W.[Ji-Wen],
Yang, M.[Ming],
Zhou, J.[Jie],
Learning Recurrent 3D Attention for Video-Based Person
Re-Identification,
IP(29), 2020, pp. 6963-6976.
IEEE DOI
2007
Feature extraction, Robustness,
Learning (artificial intelligence), Optical imaging,
recurrent model
BibRef
Rao, Y.M.[Yong-Ming],
Lu, J.W.[Ji-Wen],
Zhou, J.[Jie],
Learning Discriminative Aggregation Network for Video-Based Face
Recognition and Person Re-identification,
IJCV(127), No. 6-7, June 2019, pp. 701-718.
Springer DOI
1906
BibRef
Rao, Y.M.[Yong-Ming],
Lin, J.,
Lu, J.W.[Ji-Wen],
Zhou, J.[Jie],
Learning Discriminative Aggregation Network for Video-Based Face
Recognition,
ICCV17(3801-3810)
IEEE DOI
1802
face recognition, learning (artificial intelligence),
video signal processing, DAN method, adversarial learning,
Measurement
BibRef
Rao, Y.M.[Yong-Ming],
Lu, J.W.[Ji-Wen],
Zhou, J.[Jie],
Attention-Aware Deep Reinforcement Learning for Video Face
Recognition,
ICCV17(3951-3960)
IEEE DOI
1802
Markov processes, face recognition,
learning (artificial intelligence), video signal processing,
Markov processes
BibRef
Ding, G.D.[Guo-Dong],
Zhang, S.,
Khan, S.[Salman],
Tang, Z.M.[Zhen-Min],
Zhang, J.,
Porikli, F.M.[Fatih M.],
Feature Affinity-Based Pseudo Labeling for Semi-Supervised Person
Re-Identification,
MultMed(21), No. 11, November 2019, pp. 2891-2902.
IEEE DOI
1911
Labeling, Training,
Generative adversarial networks, Encoding,
generative modeling
BibRef
Ding, G.D.[Guo-Dong],
Khan, S.[Salman],
Tang, Z.M.[Zhen-Min],
Porikli, F.M.[Fatih M.],
Feature mask network for person re-identification,
PRL(137), 2020, pp. 91-98.
Elsevier DOI
2008
Person re-identification, Image retrieval, Network ensemble
BibRef
Wu, L.[Lin],
Wang, Y.[Yang],
Yin, H.Z.[Hong-Zhi],
Wang, M.[Meng],
Shao, L.[Ling],
Few-Shot Deep Adversarial Learning for Video-Based Person
Re-Identification,
IP(29), 2020, pp. 1233-1245.
IEEE DOI
1911
Feature extraction, Cameras, Visualization, Training, Measurement,
Recurrent neural networks, Video sequences,
adversarial learning
BibRef
Yan, Y.C.[Yi-Chao],
Qin, J.[Jie],
Chen, J.X.[Jia-Xin],
Liu, L.[Li],
Zhu, F.[Fan],
Tai, Y.[Ying],
Shao, L.[Ling],
Learning Multi-Granular Hypergraphs for Video-Based Person
Re-Identification,
CVPR20(2896-2905)
IEEE DOI
2008
Feature extraction, Correlation, Video sequences, Neural networks,
Robustness, Task analysis, Spatiotemporal phenomena
BibRef
Liao, S.C.[Sheng-Cai],
Shao, L.[Ling],
Interpretable and Generalizable Person Re-identification with
Query-adaptive Convolution and Temporal Lifting,
ECCV20(XI:456-474).
Springer DOI
2011
BibRef
Wu, L.,
Hong, R.,
Wang, Y.,
Wang, M.,
Cross-Entropy Adversarial View Adaptation for Person
Re-Identification,
CirSysVideo(30), No. 7, July 2020, pp. 2081-2092.
IEEE DOI
2007
Training, Cameras, Computer science, Probes,
Extraterrestrial measurements, Adaptation models,
entropy regularization
BibRef
Yao, R.[Rui],
Gao, C.Y.[Cun-Yuan],
Xia, S.X.[Shi-Xiong],
Zhao, J.[Jiaqi],
Zhou, Y.[Yong],
Hu, F.[Fuyuan],
GAN-based person search via deep complementary classifier with
center-constrained Triplet loss,
PR(104), 2020, pp. 107350.
Elsevier DOI
2005
Person search, Re-Identification, Pedestrian detection
BibRef
Hao, Y.[Yi],
Li, J.[Jie],
Wang, N.N.[Nan-Nan],
Gao, X.[Xinbo],
Modality adversarial neural network for visible-thermal person
re-identification,
PR(107), 2020, pp. 107533.
Elsevier DOI
2008
Cross-modality, Adversarial learning, Person re-identification
BibRef
Zhang, Y.,
Jin, Y.,
Chen, J.,
Kan, S.,
Cen, Y.,
Cao, Q.,
PGAN: Part-Based Nondirect Coupling Embedded GAN for Person
Reidentification,
MultMedMag(27), No. 3, July 2020, pp. 23-33.
IEEE DOI
2009
Feature extraction, Decoding, Couplings, Learning systems,
Task analysis, Training data
BibRef
Si, J.,
Zhang, H.,
Li, C.,
Kuen, J.,
Kong, X.,
Kot, A.C.,
Wang, G.,
Dual Attention Matching Network for Context-Aware Feature Sequence
Based Person Re-identification,
CVPR18(5363-5372)
IEEE DOI
1812
Feature extraction, Measurement, Task analysis, Visualization,
Semantics, Transforms, Computer vision
BibRef
Shen, Y.T.[Yan-Tao],
Xiao, T.[Tong],
Yi, S.[Shuai],
Chen, D.P.[Da-Peng],
Wang, X.G.[Xiao-Gang],
Li, H.S.[Hong-Sheng],
Person Re-Identification With Deep Kronecker-Product Matching and
Group-Shuffling Random Walk,
PAMI(43), No. 5, May 2021, pp. 1649-1665.
IEEE DOI
2104
BibRef
Earlier: A1, A6, A2, A3, A4, A5:
Deep Group-Shuffling Random Walk for Person Re-identification,
CVPR18(2265-2274)
IEEE DOI
1812
Probes, Deep learning, Neural networks, Training, Visualization,
Estimation, Generative adversarial networks, person re-identification.
Task analysis, Testing.
BibRef
Zhang, L.[Lei],
Liu, F.Y.[Fang-Yi],
Zhang, D.[David],
Adversarial View Confusion Feature Learning for Person
Re-Identification,
CirSysVideo(31), No. 4, April 2021, pp. 1490-1502.
IEEE DOI
2104
BibRef
Earlier: A2, A1, Only:
View Confusion Feature Learning for Person Re-Identification,
ICCV19(6638-6647)
IEEE DOI
2004
Feature extraction, Cameras, Task analysis, Learning systems,
Benchmark testing, Measurement, Adaptation models,
view-invariant features.
image recognition, image representation,
learning (artificial intelligence), video surveillance,
Measurement
BibRef
Zhao, C.,
Lv, X.,
Dou, S.,
Zhang, S.,
Wu, J.,
Wang, L.,
Incremental Generative Occlusion Adversarial Suppression Network for
Person ReID,
IP(30), 2021, pp. 4212-4224.
IEEE DOI
2104
Feature extraction, Training, Image reconstruction, Body regions,
Training data, Cameras,
occluded person re-identification
BibRef
Li, H.[Hui],
Xiao, J.[Jimin],
Sun, M.J.[Ming-Jie],
Lim, E.G.[Eng Gee],
Zhao, Y.[Yao],
Progressive sample mining and representation learning for one-shot
person re-identification,
PR(110), 2021, pp. 107614.
Elsevier DOI
2011
Re-ID, One-shot, Semi-supervised, GAN
BibRef
Song, Y.[Yue],
Bisagno, N.[Niccoló],
Hassan, S.Z.[Syed Zohaib],
Conci, N.[Nicola],
AG-GAN: An Attentive Group-Aware GAN for pedestrian trajectory
prediction,
ICPR21(8703-8710)
IEEE DOI
2105
Predictive models, Benchmark testing,
Generative adversarial networks, Trajectory, Pattern recognition, History
BibRef
Zhan, F.N.[Fang-Neng],
Zhang, C.G.[Chang-Gong],
Spatial-Aware GAN for Unsupervised Person Re-identification,
ICPR21(6889-6896)
IEEE DOI
2105
Training, Geometry, Adaptation models, Collaboration,
Generative adversarial networks, Stability analysis
BibRef
Delorme, G.[Guillaume],
Xu, Y.H.[Yi-Hong],
Lathuiliére, S.[Stéphane],
Horaud, R.[Radu],
Alameda-Pineda, X.[Xavier],
CANU-ReID:
A Conditional Adversarial Network for Unsupervised person Re-IDentification,
ICPR21(4428-4435)
IEEE DOI
2105
Training, Knowledge engineering, Visualization,
Distributed databases, Feature extraction, Cameras, Market research
BibRef
Huo, L.J.[Li-Juan],
Song, C.F.[Chun-Feng],
Liu, Z.Y.[Zheng-Yi],
Zhang, Z.X.[Zhao-Xiang],
Attentive Part-aware Networks for Partial Person Re-identification,
ICPR21(3652-3659)
IEEE DOI
2105
Training, Learning systems, Image recognition, Semantics,
Training data, Robustness, Data models,
Data augmentation
BibRef
Zhao, Z.W.[Zhong-Wei],
Song, R.[Ran],
Zhang, Q.[Qian],
Duan, P.[Peng],
Zhang, Y.[Youmei],
A Framework for Jointly Training GAN with Person Re-identification
Model,
MLCSA20(36-51).
Springer DOI
2103
BibRef
Wang, D.,
Zhang, S.,
Unsupervised Person Re-Identification via Multi-Label Classification,
CVPR20(10978-10987)
IEEE DOI
2008
Training, Computational modeling, Task analysis, Predictive models,
Robustness, Generative adversarial networks
BibRef
Zhang, Z.,
Xu, R.Y.D.[R. Y. Da],
Jiang, S.,
Li, Y.,
Huang, C.,
Deng, C.,
Illumination Adaptive Person REID Based on Teacher-Student Model and
Adversarial Training,
ICIP20(2321-2325)
IEEE DOI
2011
Lighting, Training, Adaptation models, Robustness, Cameras,
Feature extraction, Entropy, Person re-identification,
Teacher-Student model
BibRef
Bouniot, Q.,
Audigier, R.,
Loesch, A.,
Vulnerability of Person Re-Identification Models to Metric
Adversarial Attacks,
AML-CV20(3450-3459)
IEEE DOI
2008
Measurement, Training, Task analysis, Protocols, Testing,
Robustness, Perturbation methods
BibRef
Wang, H.,
Wang, G.,
Li, Y.,
Zhang, D.,
Lin, L.,
Transferable, Controllable, and Inconspicuous Adversarial Attacks on
Person Re-identification With Deep Mis-Ranking,
CVPR20(339-348)
IEEE DOI
2008
Feature extraction, Task analysis, Robustness, Visualization,
Perturbation methods, Training, Measurement
BibRef
Cheng, Z.,
Dong, Q.,
Gong, S.,
Zhu, X.,
Inter-Task Association Critic for Cross-Resolution Person
Re-Identification,
CVPR20(2602-2612)
IEEE DOI
2008
Image resolution, Training, Task analysis,
Generative adversarial networks, Cameras, Generators
BibRef
Zhou, J.,
Su, B.,
Wu, Y.,
Online Joint Multi-Metric Adaptation From Frequent Sharing-Subset
Mining for Person Re-Identification,
CVPR20(2906-2915)
IEEE DOI
2008
Testing, Measurement, Visualization, Adaptation models,
Feature extraction, Data models, Training
BibRef
Ponce-López, V.[Víctor],
Burghardt, T.[Tilo],
Sun, Y.[Yue],
Hannuna, S.[Sion],
Damen, D.[Dima],
Mirmehdi, M.[Majid],
Deep Compact Person Re-Identification with Distractor Synthesis via
Guided DC-GANs,
CIAP19(I:488-498).
Springer DOI
1909
BibRef
Wang, Z.,
Zheng, S.,
Song, M.,
Wang, Q.,
Rahimpour, A.,
Qi, H.,
advPattern: Physical-World Attacks on Deep Person Re-Identification
via Adversarially Transformable Patterns,
ICCV19(8340-8349)
IEEE DOI
2004
cameras, feature extraction, image matching,
learning (artificial intelligence), neural nets,
Perturbation methods
BibRef
Li, X.[Xiang],
Wu, A.[Ancong],
Zheng, W.S.[Wei-Shi],
Adversarial Open-World Person Re-Identification,
ECCV18(II: 287-303).
Springer DOI
1810
BibRef
Zheng, Z.,
Zheng, L.,
Yang, Y.,
Unlabeled Samples Generated by GAN Improve the Person
Re-identification Baseline in Vitro,
ICCV17(3774-3782)
IEEE DOI
1802
convolution, image representation, image sampling,
learning (artificial intelligence), neural nets,
Training data
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Domain Adaption, Cross-Doimain, Learning, Re-Identification Issues .