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.[Chunze],
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.[Chunze],
Lu, J.W.[Ji-Wen],
Wang, G.[Gang],
Zhou, J.[Jie],
Graininess-Aware Deep Feature Learning for Robust Pedestrian
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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
Tang, Y.,
Xi, Y.,
Wang, N.,
Song, B.,
Gao, X.,
CGAN-TM: A Novel Domain-to-Domain Transferring Method for Person
Re-Identification,
IP(29), 2020, pp. 5641-5651.
IEEE DOI
2005
Task analysis, Training, Cameras, Object tracking, Image recognition,
Target recognition, Surveillance, Person re-identification,
maximum mean discrepancy
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
Wang, G.,
Lai, J.,
Liang, W.,
Wang, G.,
Smoothing Adversarial Domain Attack and P-Memory Reconsolidation for
Cross-Domain Person Re-Identification,
CVPR20(10565-10574)
IEEE DOI
2008
Cameras, Task analysis, Smoothing methods, Scalability,
Benchmark testing, Clustering 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
Wei, L.,
Zhang, S.,
Gao, W.,
Tian, Q.,
Person Transfer GAN to Bridge Domain Gap for Person Re-identification,
CVPR18(79-88)
IEEE DOI
1812
Cameras, Lighting, Videos, Task analysis, Training, Testing
BibRef
Xu, F.R.[Fu-Rong],
Ma, B.P.[Bing-Peng],
Chang, H.[Hong],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Style Transfer with Adversarial Learning for Cross-Dataset Person
Re-identification,
ACCV18(VI:165-180).
Springer DOI
1906
BibRef
Deng, W.,
Zheng, L.,
Ye, Q.,
Kang, G.,
Yang, Y.,
Jiao, J.,
Image-Image Domain Adaptation with Preserved Self-Similarity and
Domain-Dissimilarity for Person Re-identification,
CVPR18(994-1003)
IEEE DOI
1812
Training, Generators, Training data,
Generative adversarial networks, Learning systems,
Estimation
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
Tracking People with Stereo, or Depth .