16.7.4.4.5 Tracking People, Re-Identification Issues, Learning

Xu, L.Q.[Li-Qun], Hogg, D.C.[David C.],
Neural Networks in Human Motion Tracking: An Experimental Study,
IVC(15), No. 8, August 1997, pp. 607-615.
Elsevier DOI 9708
BibRef
Earlier: BMVC96(Tracking). 9608
University of Abertay and University of Leeds BibRef

Nappi, M.[Michele], Wechsler, H.[Harry],
Robust re-identification using randomness and statistical learning: Quo vadis,
PRL(33), No. 14, 15 October 2012, pp. 1820-1827.
Elsevier DOI 1209
Biometrics; Evidence-based management; Face recognition; Identity management; Re-identification; Statistical learning theory BibRef

Serra, G.[Giuseppe], Grana, C.[Costantino], Manfredi, M.[Marco], Cucchiara, R.[Rita],
GOLD: Gaussians of Local Descriptors for image representation,
CVIU(134), No. 1, 2015, pp. 22-32.
Elsevier DOI 1504
Image classification BibRef

Manfredi, M.[Marco], Grana, C.[Costantino], Cucchiara, R.[Rita], Smeulders, A.W.M.[Arnold W.M.],
Segmentation models diversity for object proposals,
CVIU(158), No. 1, 2017, pp. 40-48.
Elsevier DOI 1704
BibRef
Earlier: A1, A2, A3, Only:
Learning superpixel relations for supervised image segmentation,
ICIP14(4437-4441)
IEEE DOI 1502
BibRef
Earlier: A1, A2, A3, Only:
Learning Graph Cut Energy Functions for Image Segmentation,
ICPR14(960-965)
IEEE DOI 1412
BibRef
And: A1, A2, A3, Only:
Automatic Single-Image People Segmentation and Removal for Cultural Heritage Imaging,
MM4CH13(188-197).
Springer DOI 1309
Segmentation. Accuracy. Feature extraction
See also complete system for garment segmentation and color classification, A. BibRef

Coppi, D.[Dalia], Calderara, S.[Simone], Cucchiara, R.[Rita],
Active query process for digital video surveillance forensic applications,
SIViP(9), No. 4, May 2015, pp. 749-759.
WWW Link. 1504
BibRef

Coppi, D.[Dalia], Calderara, S.[Simone], Cucchiara, R.[Rita],
Transductive People Tracking in Unconstrained Surveillance,
CirSysVideo(26), No. 4, April 2016, pp. 762-775.
IEEE DOI 1604
BibRef
Earlier:
Appearance tracking by transduction in surveillance scenarios,
AVSBS11(142-147).
IEEE DOI 1111
BibRef
And:
People appearance tracing in video by spectral graph transduction,
ARTEMIS11(920-927).
IEEE DOI 1201
covariance matrices. BibRef

Zhang, D.Y.[Dong-Yu], Liu, P.J.[Peng-Ju], Zhang, K.[Kai], Zhang, H.Z.[Hong-Zhi], Wang, Q.[Qing], Jing, X.Y.[Xiao-Yuan],
Class Relatedness Oriented-Discriminative Dictionary Learning for Multiclass Image Classification,
PR(59), No. 1, 2016, pp. 168-175.
Elsevier DOI 1609
Dictionary learning
See also Learning Robust and Discriminative Low-Rank Representations for Face Recognition with Occlusion. BibRef

Jing, X.Y.[Xiao-Yuan], Zhu, X.K.[Xiao-Ke], Wu, F.[Fei], Hu, R.M.[Rui-Min], You, X.G.[Xin-Ge], Wang, Y., Feng, H., Yang, J.Y.,
Super-Resolution Person Re-Identification with Semi-Coupled Low-Rank Discriminant Dictionary Learning,
IP(26), No. 3, March 2017, pp. 1363-1378.
IEEE DOI 1703
Cameras
See also Learning Robust and Discriminative Low-Rank Representations for Face Recognition with Occlusion. BibRef

Jing, X.Y.[Xiao-Yuan], Zhu, X.K.[Xiao-Ke], Wu, F.[Fei], You, X.G.[Xin-Ge], Liu, Q.L.[Qing-Long], Yue, D.[Dong], Hu, R.M.[Rui-Min], Xu, B.[Baowen],
Super-Resolution Person Re-Identification with Semi-Coupled Low-Rank Discriminant Dictionary Learning,
CVPR15(695-704)
IEEE DOI 1510
BibRef

Zhu, X.K.[Xiao-Ke], Jing, X.Y.[Xiao-Yuan], Yang, L.[Liang], You, X.G.[Xin-Ge], Chen, D.[Dan], Gao, G.W.[Guang-Wei], Wang, Y.H.[Yun-Hong],
Semi-Supervised Cross-View Projection-Based Dictionary Learning for Video-Based Person Re-Identification,
CirSysVideo(28), No. 10, October 2018, pp. 2599-2611.
IEEE DOI 1811
Videos, Cameras, Dictionaries, Feature extraction, Training, Computer aided instruction, Labeling, cross-view learning BibRef

Wang, J.[Jin], Sang, N.[Nong], Wang, Z.[Zheng], Gao, C.X.[Chang-Xin],
Similarity Learning with Top-heavy Ranking Loss for Person Re-identification,
SPLetters(23), No. 1, January 2016, pp. 84-88.
IEEE DOI 1601
image matching BibRef

Lin, W.Y.[Wei-Yao], Shen, Y.[Yang], Yan, J.C.[Jun-Chi], Xu, M.L.[Ming-Liang], Wu, J.X.[Jian-Xin], Wang, J.D.[Jing-Dong], Lu, K.[Ke],
Learning Correspondence Structures for Person Re-Identification,
IP(26), No. 5, May 2017, pp. 2438-2453.
IEEE DOI 1704
BibRef
Earlier: A2, A1, A3, A5, A5, A6, Only:
Person Re-Identification with Correspondence Structure Learning,
ICCV15(3200-3208)
IEEE DOI 1602
Cameras BibRef

Zheng, L.[Liang], Shen, L.Y.[Li-Yue], Tian, L.[Lu], Wang, S.J.[Sheng-Jin], Wang, J.D.[Jing-Dong], Tian, Q.[Qi],
Scalable Person Re-identification: A Benchmark,
ICCV15(1116-1124)
IEEE DOI 1602
Benchmark testing BibRef

Zhao, R.[Rui], Ouyang, W.L.[Wan-Li], Wang, X.G.[Xiao-Gang],
Person Re-Identification by Saliency Learning,
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], Yuan, Z.J.[Ze-Jian], Wang, J.D.[Jing-Dong], Chen, B.D.[Ba-Dong], Hua, G.[Gang], Zheng, N.N.[Nan-Ning],
Exemplar-Guided Similarity Learning on Polynomial Kernel Feature Map for Person Re-identification,
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 person re-identification,
CVPR15(1565-1573)
IEEE DOI 1510
BibRef

Chen, G., Lu, J.W.[Ji-Wen], Feng, J.J.[Jian-Jiang], Zhou, J.[Jie],
Localized multi-kernel discriminative canonical correlation analysis for video-based person re-identification,
ICIP17(111-115)
IEEE DOI 1803
Cameras, Correlation, Kernel, Manifolds, Measurement, Optimization, Videos, Person re-identification, canonical correlation analysis, multiple kernel learning. BibRef

Dong, H.S.[Hu-Sheng], Gong, S.R.[Sheng-Rong], Liu, C.P.[Chun-Ping], Ji, Y.[Yi], Zhong, S.[Shan],
Large margin relative distance learning for person re-identification,
IET-CV(11), No. 6, September 2017, pp. 455-462.
DOI Link 1709
BibRef

An, L., Qin, Z., Chen, X., Yang, S.,
Multi-Level Common Space Learning for Person Re-Identification,
CirSysVideo(28), No. 8, August 2018, pp. 1777-1787.
IEEE DOI 1808
Cameras, Measurement, Feature extraction, Image color analysis, Probes, Lighting, Surveillance, Person re-identification, group sparse representation BibRef

Karanam, S., Wu, Z., Radke, R.J.,
Learning Affine Hull Representations for Multi-Shot Person Re-Identification,
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, video analytics BibRef

Wang, H.X.[Han-Xiao], Zhu, X.T.[Xia-Tian], Gong, S.G.[Shao-Gang], Xiang, T.[Tao],
Person Re-identification in Identity Regression Space,
IJCV(126), No. 12, December 2018, pp. 1288-1310.
Springer DOI 1811
BibRef

Li, W.[Wei], Gong, S.G.[Shao-Gang], Zhu, X.T.[Xia-Tian],
Hierarchical distillation learning for scalable person search,
PR(114), 2021, pp. 107862.
Elsevier DOI 2103
Person search, Person re-identification, Person detection, Knowledge distillation, Scalability, Model inference efficiency BibRef

Li, M.X.[Min-Xian], Zhu, X.T.[Xia-Tian], 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], Zhang, Z.X.[Zhao-Xiang], Zhang, J.[Jian],
Multi-Pseudo Regularized Label for Generated Data in Person Re-Identification,
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 Re-Identification,
SPLetters(27), 2020, pp. 391-395.
IEEE DOI 2004
Person re-identification, generated data, sparse pseudo label BibRef

Xian, Y.Q.[Yu-Qiao], Hu, H.F.[Hai-Feng],
Enhanced multi-dataset transfer learning method for unsupervised person re-identification using co-training strategy,
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 BibRef

Subramanyam, A.V., Gupta, V., 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 learning,
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 analysis,
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 via multi-loss training,
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 constraints,
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 re-identification via significance-aware attention,
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 Exploration,
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

Huang, Y.[Yan], Xu, J.S.[Jing-Song], Wu, Q.[Qiang], Zhong, Y.[Yi], Zhang, P.[Peng], Zhang, Z.X.[Zhao-Xiang],
Beyond Scalar Neuron: Adopting Vector-Neuron Capsules for Long-Term Person Re-Identification,
CirSysVideo(30), No. 10, October 2020, pp. 3459-3471.
IEEE DOI 2010
Cameras, Surveillance, Neurons, Internet, Security, Lighting, Face, Person re-identification, long-term scenario, cloth change, vector-neuron capsules 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 BibRef

Huang, Y.[Yewen], Lian, S.C.[Si-Cheng], Hu, H.F.[Hai-Feng], Chen, D.[Dihu], Su, T.[Tao],
Multiscale Omnibearing Attention Networks for Person Re-Identification,
CirSysVideo(31), No. 5, 2021, pp. 1790-1803.
IEEE DOI 2105
BibRef

Han, J., Li, Y., Wang, S.,
Adaptively Leverage Unlabeled Tracklets Based on Part Attention Model for Few-Example Re-ID,
SPLetters(27), 2020, pp. 2074-2078.
IEEE DOI 2012
Training, Adaptation models, Data models, Reliability, Estimation, Noise measurement, Probes, Person re-ID, few-example, noisy labels BibRef

Zhou, Q., Fan, H., Yang, H., Su, H., Zheng, S., Wu, S., Ling, H.,
Robust and Efficient Graph Correspondence Transfer for Person Re-Identification,
IP(30), 2021, pp. 1623-1638.
IEEE DOI 2101
Visualization, Semantics, Training, Pattern matching, Context modeling, Measurement, Cameras, correspondence template ensemble BibRef

Liu, Y., Zhou, W., Liu, J., Qi, G.J., Tian, Q., Li, H.,
An End-to-End Foreground-Aware Network for Person Re-Identification,
IP(30), 2021, pp. 2060-2071.
IEEE DOI 2101
Feature extraction, Cameras, Data models, Body regions, Training, Visualization, Spatiotemporal phenomena, attention BibRef

Wang, X., Liu, M., Raychaudhuri, D.S., Paul, S., Wang, Y., Roy-Chowdhury, A.K.,
Learning Person Re-Identification Models From Videos With Weak Supervision,
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 BibRef

Liu, G.Q.[Gui-Qing], Wu, J.Z.[Jin-Zhao],
Video-based person re-identification by intra-frame and inter-frame graph neural network,
IVC(106), 2021, pp. 104068.
Elsevier DOI 2102
Person re-identification, Graph neural network, Intra and inter frame, Body part, Video matching BibRef

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 Visible-Thermal Person Re-Identification,
SPLetters(28), 2021, pp. 653-657.
IEEE DOI 2104
Training, Measurement, Testing, Organizations, Neck, Focusing, Dual-granularity triplet loss, visible-thermal person re-identification BibRef

Huang, Y.[Yan], Wu, Q.[Qiang], Xu, J.S.[Jing-Song], Zhong, Y.[Yi], Zhang, Z.X.[Zhao-Xiang],
Unsupervised Domain Adaptation with Background Shift Mitigating for Person Re-Identification,
IJCV(129), No. 7, July 2021, pp. 2244-2263.
Springer DOI 2106
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Nikhal, K.[Kshitij], 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 BibRef

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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 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 BibRef

Zang, X.H.[Xiang-Hao], Li, G.[Ge], Gao, W.[Wei], Shu, X.J.[Xiu-Jun],
Exploiting robust unsupervised video person re-identification,
IET-IPR(16), No. 3, 2022, pp. 729-741.
DOI Link 2202
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Zhong, Y.J.[Ying-Ji], 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 BibRef

Kiran, M.[Madhu], Bhuiyan, A.[Amran], Nguyen-Meidine, L.T.[Le Thanh], Blais-Morin, L.A.[Louis-Antoine], Ben Ayed, I.[Ismail], Granger, E.[Eric],
Flow guided mutual attention for person re-identification,
IVC(113), 2021, pp. 104246.
Elsevier DOI 2108
Video surveillance, Person re-identification, Optical flow, Metric learning, Attention mechanisms BibRef

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 BibRef

Zhang, Z.Y.[Zi-Yue], Jiang, S.[Shuai], Huang, C.Z.[Cong-Zhentao], Li, Y.[Yang], Xu, R.Y.D.[Richard Yi Da],
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 BibRef

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 BibRef

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 BibRef

Sun, R.[Rui], Liang, Q.L.[Qi-Li], Yang, Z.[Zi], Zhao, Z.H.[Zheng-Hui], Zhang, X.D.[Xu-Dong],
Triplet Attention Network for Video-Based Person Re-Identification,
IEICE(E104-D), No. 10, October 2021, pp. 1775-1779.
WWW Link. 2110
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Shao, Z.F.[Zhen-Feng], Wang, J.M.[Jia-Ming], Lu, T.[Tao], Zhang, R.Q.[Rui-Qian], Huang, X.[Xiao], Lv, X.W.[Xian-Wei],
Internal and external spatial-temporal constraints for person reidentification,
JVCIR(80), 2021, pp. 103302.
Elsevier DOI 2110
Person reidentification, Convolution neural network, Attention mechanism, Spatial-temporal constraint BibRef

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 BibRef

Raj, S.S.[S. Sridhar], Prasad, M.V.N.K.[Munaga V.N.K.], Balakrishnan, R.[Ramadoss],
Spatio-Temporal association rule based deep annotation-free clustering (STAR-DAC) for unsupervised person re-identification,
PR(122), 2022, pp. 108287.
Elsevier DOI 2112
Unsupervised person re-identification, Clustering, Labeling, Spatio-temporal, Deep learning BibRef

Zhang, C.Y.[Chen-Yang], Tang, Y.Q.[Yong-Qiang], Zhang, Z.Z.[Zhi-Zhong], Li, D.[Ding], Yang, X.B.[Xue-Bing], Zhang, W.S.[Wen-Sheng],
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 BibRef

Cheng, G.[Guoan], Shi, J.Y.[Jun-Yu], Wang, H.[Hao], Chen, L.[Long], Guo, J.X.[Jia-Xi], Wang, S.[Shengke],
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 BibRef

Wei, W.Y.[Wen-Yu], Yang, W.Z.[Wen-Zhong], Zuo, E.[Enguang], Ren, Q.[Qiuru], Chen, Q.[Qiuchang],
Multi-branch network with hierarchical bilinear pooling for person reidentification,
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 Method for Person Re-Identification,
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], Ai, H.Z.[Hai-Zhou], 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], Zuo, E.[Enguang], Qian, Y.Y.[Yun-Yun], 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 BibRef

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 BibRef

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 BibRef

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.[Jianmin], 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 BibRef

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

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
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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 BibRef

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.[Tianyang], 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
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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.[Yuhao], Zheng, Y.[Yuhui],
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

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.[Qiaoyuan], 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

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

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.[Haowei], 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.[Jianmin], 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.[Tianyu], 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.[Cong-Zhentao], 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

Tay, C.P.[Chiat-Pin], Yap, K.H.[Kim-Hui],
APNET: Attribute Parsing Network for Person Re-Identification,
ICIP21(1144-1148)
IEEE DOI 2201
Image color analysis, Neurons, Clothing, Feature extraction, Person re-identification, attribute learning, saliency map 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.[Dengpan], Chen, D.D.[Dong-Dong], Bao, J.[Jianmin], 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

Weber, M., Bauml, M., Stiefelhagen, R.[Rainer],
Part-based clothing segmentation for person retrieval,
AVSBS11(361-366).
IEEE DOI 1111
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 .