16.7.4.4.4 Tracking People, Re-Identification Issues, Learning

Chapter Contents (Back)
Motion, Human. Tracking. Learning. Neural Networks. Re-Identification.
See also Convolutional Neural Network, CNN, Re-Identification Issues, Pedestrian Tracking.
See also Metric Learning, Re-Identification Issues.
See also Adversarial Learning, GAN, Re-Identification Issues, Pedestrian Tracking.
See also Domain Adaption, Cross-Doimain, Learning, Re-Identification Issues.

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.[Xinge], 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.[Yichao], 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.[Qiaoyuan], 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, Computer architecture, Task analysis, Cameras, video surveillance 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.[Jinzhao],
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

Uner, O.C.[Onur Can], Aslan, C.[Cem], Ercan, B.[Burak], Ates, T.[Tayfun], Celikcan, U.[Ufuk], Erdem, A.[Aykut], Erdem, E.[Erkut],
Synthetic18K: Learning Better Representations for Person Re-ID and Attribute Recognition from 1.4 Million Synthetic Images,
SP:IC(97), 2021, pp. 116335.
Elsevier DOI 2107
Person re-identification, Attribute recognition, Synthetic data BibRef

Yang, X.[Xi], Liu, L.C.[Liang-Chen], Wang, N.N.[Nan-Nan], Gao, X.[Xinbo],
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.[Yaowei], 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

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, Computer architecture, Benchmark testing BibRef

Zhang, Z.[Ziyue], 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


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
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Wang, L.[Li], Fan, B.[Baoyu], 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
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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, Computer architecture, 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
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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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Huang, Y., Zha, Z., Fu, X., Hong, R., Li, L.,
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

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
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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, computer vision, 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

Zhou, S., Wang, F., Huang, Z., Wang, J.,
Discriminative Feature Learning With Consistent Attention Regularization for Person Re-Identification,
ICCV19(8039-8048)
IEEE DOI 2004
feature extraction, learning (artificial intelligence), neural nets, consistent attention regularizer, Computer vision 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
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Meng, J.[Jingke], Wu, S.[Sheng], Zheng, W.S.[Wei-Shi],
Weakly Supervised Person Re-Identification,
CVPR19(760-769).
IEEE DOI 2002
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Yang, W.J.[Wen-Jie], Huang, H.J.[Hou-Jing], Zhang, Z.[Zhang], Chen, X.[Xiaotang], 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
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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.[Qize], 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.[Ziyan], Radke, R.J.[Richard J.],
Re-Identification With Consistent Attentive Siamese Networks,
CVPR19(5728-5737).
IEEE DOI 2002
BibRef

Sun, Y.[Yifan], 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
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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, Computer architecture, 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.[Shaozi], 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
Computer architecture, 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.[Yaowei], 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).
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Can feature-based inductive transfer learning help person re-identification?,
ICIP13(2812-2816)
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Pedestrian's Trajectory Forecast in Public Traffic with Artificial Neural Networks,
ICPR14(4110-4115)
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Dynamic Integration of Generalized Cues for Person Tracking,
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AVSBS11(291-296).
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AVSBS11(525-526).
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Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Metric Learning, Re-Identification Issues .


Last update:Oct 24, 2021 at 16:35:58