17.1.3.5.8 Adversarial Learning, GAN, Re-Identification Issues, Pedestrian Tracking

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.Q.[Jia-Qi], Zhou, Y.[Yong], Hu, F.Y.[Fu-Yuan],
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

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

Liu, Z.[Zhipu], Zhang, L.[Lei], Zhang, D.[David],
Neural Image Parts Group Search for Person Re-Identification,
CirSysVideo(33), No. 6, June 2023, pp. 2724-2737.
IEEE DOI 2306
Semantics, Genetic algorithms, Training, Optimization, Search problems, Random access memory, Deep learning, relational attention module BibRef

Zhang, L.[Lei], Liu, Z.[Zhipu], Zhang, W.S.[Wen-Sheng], Zhang, D.[David],
Style Uncertainty Based Self-Paced Meta Learning for Generalizable Person Re-Identification,
IP(32), 2023, pp. 2107-2119.
IEEE DOI 2304
Training, Semantics, Data models, Generative adversarial networks, Adaptation models, Task analysis, Gaussian noise, distance-graph alignment 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

Li, H.F.[Hua-Feng], Dong, N.[Neng], Yu, Z.T.[Zheng-Tao], Tao, D.P.[Da-Peng], Qi, G.Q.[Guan-Qiu],
Triple Adversarial Learning and Multi-View Imaginative Reasoning for Unsupervised Domain Adaptation Person Re-Identification,
CirSysVideo(32), No. 5, May 2022, pp. 2814-2830.
IEEE DOI 2205
Feature extraction, Cameras, Cognition, Data mining, Robustness, Training, Supervised learning, Person re-identification, triple adversarial learning BibRef

Qi, L.[Lei], Wang, L.[Lei], Huo, J.[Jing], Shi, Y.H.[Ying-Huan], Geng, X.[Xin], Gao, Y.[Yang],
Adversarial Camera Alignment Network for Unsupervised Cross-Camera Person Re-Identification,
CirSysVideo(32), No. 5, May 2022, pp. 2921-2936.
IEEE DOI 2205
Cameras, Task analysis, Software, Noise measurement, Manuals, Lighting, Labeling, Adversarial camera alignment network, unsupervised cross-camera person re-identification BibRef

Wei, J.[Jiwei], Pan, C.[Chen], He, S.Y.[Shi-Yuan], Wang, G.Q.[Guo-Qing], Yang, Y.[Yang], Shen, H.T.[Heng Tao],
Towards Robust Person Re-Identification by Adversarial Training With Dynamic Attack Strategy,
MultMed(26), 2024, pp. 10367-10380.
IEEE DOI 2410
Training, Robustness, Perturbation methods, Measurement, Task analysis, Identification of persons, Security, person re-identification BibRef

Gao, J.Y.[Jun-Yao], Jiang, X.Y.[Xin-Yang], Dou, S.G.[Shu-Guang], Li, D.S.[Dong-Sheng], Miao, D.Q.[Duo-Qian], Zhao, C.R.[Cai-Rong],
Re-ID-leak: Membership Inference Attacks Against Person Re-identification,
IJCV(132), No. 10, October 2024, pp. 4673-4687.
Springer DOI 2410
BibRef

Ang, E.P.W.[Eugene P.W.], Lin, S.[Shan], Ahuja, R.[Rahul], Ahmed, N.[Nemath], Kot, A.C.[Alex C.],
Adversarial Pairwise Reverse Attention for Camera Performance Imbalance in Person Re-Identification: New Dataset And Metrics,
ICIP22(1421-1425)
IEEE DOI 2211
Measurement, Training, Surveillance, Benchmark testing, Cameras, Person Re-identification, Data Imbalance, Adversarial Learning, Attention BibRef

Sun, H., Zhao, Z., He, Z.,
Reciprocal Learning Networks for Human Trajectory Prediction,
CVPR20(7414-7423)
IEEE DOI 2008
Trajectory, Training, Predictive models, Generative adversarial networks, Semantics, Neural networks, Task analysis 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

Rami, H.[Hamza], Giraldo, J.H.[Jhony H.], Winckler, N.[Nicolas], Lathuilière, S.[Stéphane],
Privacy-preserving Adaptive Re-identification Without Image Transfer,
ECCV24(LII: 95-111).
Springer DOI 2412
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 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 -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Domain Adaption, Cross-Domain, Learning, Re-Identification Issues .