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computer vision
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Springer DOI
1011
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Lu, H.C.[Hu-Chuan],
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Chen, Y.W.[Yen-Wei],
Robust Tracking Based on Pixel-Wise Spatial Pyramid and Biased Fusion,
ACCV10(IV: 165-176).
Springer DOI
1011
BibRef
Yang, F.[Fan],
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Yang, M.H.[Ming-Hsuan],
Robust Visual Tracking via Multiple Kernel Boosting With Affinity
Constraints,
CirSysVideo(24), No. 2, February 2014, pp. 242-254.
IEEE DOI
1403
object tracking
BibRef
Ding, S.Y.[Sheng-Yong],
Lin, L.[Liang],
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Deep feature learning with relative distance comparison for person
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PR(48), No. 10, 2015, pp. 2993-3003.
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1507
Person re-identification
BibRef
Zhang, K.H.[Kai-Hua],
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Robust Visual Tracking via Convolutional Networks Without Training,
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1604
Computer architecture
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Orts-Escolano, S.[Sergio],
Pedestrian Movement Direction Recognition Using Convolutional Neural
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ITS(18), No. 12, December 2017, pp. 3540-3548.
IEEE DOI
1712
Biological neural networks, Estimation, Histograms, Neurons,
Training, Trajectory, Pedestrian detection,
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Yang, Q.[Qian],
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JVCIR(57), 2018, pp. 172-175.
Elsevier DOI
1812
Pedestrian tracking, Convolutional neural networks, Optical flow
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Elsevier DOI
1705
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Earlier:
A coarse-to-fine deep learning for person re-identification,
WACV16(1-7)
IEEE DOI
1606
Person re-identification.
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BibRef
McLaughlin, N.,
del Rincon, J.M.[J. Martinez],
Miller, P.C.,
Person Reidentification Using Deep Convnets With Multitask Learning,
CirSysVideo(27), No. 3, March 2017, pp. 525-539.
IEEE DOI
1703
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Earlier:
Data-augmentation for reducing dataset bias in person
re-identification,
AVSS15(1-6)
IEEE DOI
1511
image processing
BibRef
Wang, J.[Jin],
Wang, Z.[Zheng],
Gao, C.X.[Chang-Xin],
Sang, N.[Nong],
Huang, R.,
DeepList: Learning Deep Features With Adaptive Listwise Constraint
for Person Reidentification,
CirSysVideo(27), No. 3, March 2017, pp. 513-524.
IEEE DOI
1703
Computer architecture
BibRef
Chen, S.Z.,
Guo, C.C.,
Lai, J.H.,
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IP(25), No. 5, May 2016, pp. 2353-2367.
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1604
Algorithm design and analysis
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PR(86), 2019, pp. 143-155.
Elsevier DOI
1811
Person re-identification, Visual attention, Pose estimation,
Deep neural networks
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Meng, D.Y.[De-Yu],
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PR(76), No. 1, 2018, pp. 739-751.
Elsevier DOI
1801
Person re-identification
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Lin, J.,
Ren, L.,
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Feng, J.J.[Jian-Jiang],
Zhou, J.[Jie],
Consistent-Aware Deep Learning for Person Re-identification in a
Camera Network,
CVPR17(3396-3405)
IEEE DOI
1711
Cameras, Image color analysis, Indexes, Lighting, Machine learning,
Measurement, Optimal, matching
BibRef
Cheng, D.[De],
Gong, Y.H.[Yi-Hong],
Chang, X.J.[Xiao-Jun],
Shi, W.W.[Wei-Wei],
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person re-identification,
PR(82), 2018, pp. 94-104.
Elsevier DOI
1806
Person re-identification, Structured, Graph Laplacian, Deep learning
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Hu, L.[Liang],
Hong, C.Q.[Chao-Qun],
Zeng, Z.Q.A.[Zhi-Qi-Ang],
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RealTimeIP(14), No. 1, January 2018, pp. 947-954.
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Liu, Y.G.[Yong-Ge],
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JVCIR(58), 2019, pp. 46-52.
Elsevier DOI
1901
Deep learning, Fusion strategy, Re-identification
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Yu, P.J.[Pei-Jia],
Zhao, Y.[Yong],
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Xie, X.Y.[Xiao-Yao],
Pedestrian detection using multi-channel visual feature fusion by
learning deep quality model,
JVCIR(63), 2019, pp. 102579.
Elsevier DOI
1909
Convolutional neural networks, Pedestrian detection,
VGG-16 net, RA block, Faster R-CNN, Quality model
BibRef
Zheng, Z.,
Zheng, L.,
Yang, Y.,
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CirSysVideo(29), No. 10, October 2019, pp. 3037-3045.
IEEE DOI
1910
convolutional neural nets, feature extraction, image matching,
image retrieval, learning (artificial intelligence), pedestrians,
deep learning
BibRef
Shen, C.,
Qi, G.,
Jiang, R.,
Jin, Z.,
Yong, H.,
Chen, Y.,
Hua, X.,
Sharp Attention Network via Adaptive Sampling for Person
Re-Identification,
CirSysVideo(29), No. 10, October 2019, pp. 3016-3027.
IEEE DOI
1910
convolutional neural nets, feature extraction, image sampling,
learning (artificial intelligence), sharp attention network,
CNN
BibRef
Zhang, W.[Wei],
Yu, X.D.[Xiao-Dong],
He, X.Y.[Xuan-Yu],
Learning Bidirectional Temporal Cues for Video-Based Person
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CirSysVideo(28), No. 10, October 2018, pp. 2768-2776.
IEEE DOI
1811
Feature extraction, Measurement, Optical filters, Cameras,
Video sequences, Recurrent neural networks, surveillance
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Zhang, W.[Wei],
Hu, S.N.[Sheng-Nan],
Liu, K.[Kan],
Zha, Z.J.[Zheng-Jun],
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CirSysVideo(29), No. 8, August 2019, pp. 2442-2452.
IEEE DOI
1908
Legged locomotion, Feature extraction, Task analysis, Cameras,
Video sequences, Training, Data mining, CNN
BibRef
Chen, Y.Q.[Yi-Qiang],
Duffner, S.[Stefan],
Stoian, A.[Andrei],
Dufour, J.Y.[Jean-Yves],
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Deep and low-level feature based attribute learning for person
re-identification,
IVC(79), 2018, pp. 25-34.
Elsevier DOI
1811
Person re-identification, Soft-biometrics,
Pedestrian attributes, Convolutional neural network
BibRef
Yao, H.T.[Han-Tao],
Zhang, S.L.[Shi-Liang],
Hong, R.C.[Ri-Chang],
Zhang, Y.D.[Yong-Dong],
Xu, C.S.[Chang-Sheng],
Tian, Q.[Qi],
Deep Representation Learning With Part Loss for Person
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IP(28), No. 6, June 2019, pp. 2860-2871.
IEEE DOI
1905
image classification, image representation,
learning (artificial intelligence), neural nets,
convolutional neural networks
BibRef
Li, Y.X.[Yong-Xi],
Tang, W.Z.[Wen-Zhong],
Wang, S.[Shuai],
Qian, S.S.[Sheng-Sheng],
Xu, C.S.[Chang-Sheng],
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IEEE DOI Code:
WWW Link.
2408
Feature extraction, Task analysis, Self-supervised learning,
Pedestrians, Calibration, Semantics, calibration
BibRef
Wu, Y.[Yu],
Lin, Y.T.[Yu-Tian],
Dong, X.Y.[Xuan-Yi],
Yan, Y.[Yan],
Bian, W.[Wei],
Yang, Y.[Yi],
Progressive Learning for Person Re-Identification With One Example,
IP(28), No. 6, June 2019, pp. 2872-2881.
IEEE DOI
1905
convolutional neural nets, image sampling,
learning (artificial intelligence), index-labeled data,
few-example learning
BibRef
Wu, L.,
Wang, Y.,
Gao, J.,
Li, X.,
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MultMed(21), No. 6, June 2019, pp. 1412-1424.
IEEE DOI
1906
Feature extraction, Measurement, Visualization,
Spatiotemporal phenomena, Convolution,
visual attention
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Shao, J.[Jie],
Video-based person re-identification via spatio-temporal attentional
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PRL(117), 2019, pp. 153-160.
Elsevier DOI
1901
Video-based person re-identification, Two-stream fusion,
Spatio-temporal attention network, Heterogenous feature fusion
BibRef
Li, D.G.[Dian-Gang],
Gong, Y.H.[Yi-Hong],
Cheng, D.[De],
Shi, W.W.[Wei-Wei],
Tao, X.Y.[Xiao-Yu],
Chang, X.Y.[Xin-Yuan],
Consistency-Preserving deep hashing for fast person re-identification,
PR(94), 2019, pp. 207-217.
Elsevier DOI
1906
Convolutional neural network, Fast person re-identification,
Deep hashing, Consistency preservation
BibRef
Zheng, L.,
Huang, Y.,
Lu, H.,
Yang, Y.,
Pose-Invariant Embedding for Deep Person Re-Identification,
IP(28), No. 9, Sep. 2019, pp. 4500-4509.
IEEE DOI
1908
affine transforms, convolutional neural nets, face recognition,
feature extraction, image matching, image representation,
person re-identification
BibRef
Zhou, S.P.[San-Ping],
Wang, J.J.[Jin-Jun],
Meng, D.Y.[De-Yu],
Liang, Y.D.[Yu-Dong],
Gong, Y.H.[Yi-Hong],
Zheng, N.N.[Nan-Ning],
Discriminative Feature Learning With Foreground Attention for Person
Re-Identification,
IP(28), No. 9, Sep. 2019, pp. 4671-4684.
IEEE DOI
1908
convolutional neural nets, image representation,
object detection, regression analysis, supervised learning,
foreground attentive feature learning
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Zhang, Q.D.[Qin-Dong],
Zhou, S.P.[San-Ping],
Wang, J.J.[Jin-Jun],
Learning Generic Feature Representations with Adversarial
Regularization for Person Re-Identification,
ICIP21(2358-2362)
IEEE DOI
2201
Training, Feature extraction, Person Re-identification,
Adversarial Learning, Deep Learning
BibRef
Zhou, S.P.[San-Ping],
Wang, F.[Fei],
Huang, Z.Y.[Ze-Yi],
Wang, J.J.[Jin-Jun],
Discriminative Feature Learning With Consistent Attention
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ICCV19(8039-8048)
IEEE DOI
2004
feature extraction, learning (artificial intelligence),
neural nets, consistent attention regularizer
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Improved person re-identification based on saliency and semantic
parsing with deep neural network models,
IVC(92), 2019, pp. 103809.
Elsevier DOI
1912
Person re-identification, Deep learning,
Multi-clue guided learning, Human semantic parsing,
Convolutional neural networks
BibRef
Fan, X.[Xing],
Jiang, W.[Wei],
Luo, H.[Hao],
Fei, M.J.[Meng-Juan],
SphereReID: Deep hypersphere manifold embedding for person
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JVCIR(60), 2019, pp. 51-58.
Elsevier DOI
1903
Person re-identification, Classification, Feature embedding,
CNN, Hypersphere
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Luo, H.[Hao],
Jiang, W.[Wei],
Zhang, X.[Xuan],
Fan, X.[Xing],
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PR(94), 2019, pp. 53-61.
Elsevier DOI
1906
Person re-identification, CNNs, Dynamically alignment
BibRef
Zhang, W.,
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Xu, X.,
Liu, Z.,
Ji, X.,
Learning Intra-Video Difference for Person Re-Identification,
CirSysVideo(29), No. 10, October 2019, pp. 3028-3036.
IEEE DOI
1910
feature extraction, image matching, image sequences,
iterative methods, learning (artificial intelligence),
CNN
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Song, W.,
Li, S.,
Chang, T.,
Hao, A.,
Zhao, Q.,
Qin, H.,
Context-Interactive CNN for Person Re-Identification,
IP(29), 2020, pp. 2860-2874.
IEEE DOI
2001
Task analysis, Reinforcement learning, Feature extraction, Videos,
Cameras, Context modeling, Clutter, Person re-identification,
context-critic network
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End-to-end training of CNN ensembles for person re-identification,
PR(104), 2020, pp. 107319.
Elsevier DOI
2005
Deep networks, Ensemble learning, Person re-identification
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Huang, T.J.[Tie-Jun],
Multi-Scale Temporal Cues Learning for Video Person Re-Identification,
IP(29), 2020, pp. 4461-4473.
IEEE DOI
2003
Video Person ReID, Convolutional Neural Networks,
Spatial Temporal Feature Learning
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Curriculum Enhanced Supervised Attention Network for Person
Re-Identification,
SPLetters(27), 2020, pp. 1665-1669.
IEEE DOI
1806
Training, Feature extraction, Convolution, Detectors, Correlation,
Machine learning, Complexity theory,
Person re-identification supervised attention curriculum learning
BibRef
Luo, H.,
Jiang, W.,
Fan, X.,
Zhang, C.,
STNReID: Deep Convolutional Networks With Pairwise Spatial
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MultMed(22), No. 11, November 2020, pp. 2905-2913.
IEEE DOI
2010
Feature extraction, Task analysis, Training, Deep learning,
Computational modeling, Fans, Image reconstruction,
deep learning
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Hu, H.F.[Hai-Feng],
Chen, D.[Dihu],
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Three-Dimension Transmissible Attention Network for Person
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CirSysVideo(30), No. 12, December 2020, pp. 4540-4553.
IEEE DOI
2012
Feature extraction, Convolution,
Data mining, Visualization, Image recognition, feature representation
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Zhang, L.[Lei],
Bit-Scalable Deep Hashing With Regularized Similarity Learning for
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IEEE DOI
1512
cryptography
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Zhang, D.Y.[Dong-Yu],
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Dong, Z.J.[Zhen-Jiang],
Cai, Z.Q.[Zhao-Quan],
Image-to-Video Person Re-Identification With Temporally Memorized
Similarity Learning,
CirSysVideo(28), No. 10, October 2018, pp. 2622-2632.
IEEE DOI
1811
Feature extraction, Measurement, Video sequences,
Image color analysis, Histograms, Probes, Cameras, Person re-id,
LSTM
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Zhao, C.R.[Cai-Rong],
Wang, X.K.[Xue-Kuan],
Zuo, W.M.[Wang-Meng],
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Shao, L.[Ling],
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PR(97), 2020, pp. 107014.
Elsevier DOI
1910
Person re-identification, Feature extraction, Similarity learning
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Zhao, C.R.[Cai-Rong],
Lv, X.B.[Xin-Bi],
Zhang, Z.[Zhang],
Zuo, W.M.[Wang-Meng],
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Deep Fusion Feature Representation Learning With Hard Mining
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MultMed(22), No. 12, December 2020, pp. 3180-3195.
IEEE DOI
2011
Feature extraction, Measurement, Training, Optimization,
Computational modeling, Lighting, Task analysis,
hard mining center-triplet loss
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Zhao, C.R.[Cai-Rong],
Chen, K.[Kang],
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Multilevel triplet deep learning model for person re-identification,
PRL(117), 2019, pp. 161-168.
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1901
Multilevel feature extraction, Triplet architecture, Person re-identification
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Deep asymmetric video-based person re-identification,
PR(93), 2019, pp. 430-441.
Elsevier DOI
1906
Person re-identification, Visual surveillance
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Bai, X.[Xiang],
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Deep-Person: Learning discriminative deep features for person
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PR(98), 2020, pp. 107036.
Elsevier DOI
1911
Person Re-ID, LSTM, Triplet loss, End-to-end
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Li, H.F.[Hua-Feng],
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IP(29), 2020, pp. 7345-7358.
IEEE DOI
2007
Dictionaries, Feature extraction, Cameras, Image coding,
Deep learning, Visualization, Person re-identification,
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Tagore, N.K.[Nirbhay Kumar],
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Person re-identification from appearance cues and deep Siamese
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JVCIR(75), 2021, pp. 103029.
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2103
Hierarchical re-identification approach,
Color-based clustering, Silhouette part-based analysis,
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Chen, X.,
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Lu, X.,
Bidirectional Interaction Network for Person Re-Identification,
IP(30), 2021, pp. 1935-1948.
IEEE DOI
2101
Feature extraction, Convolution, Pose estimation, Task analysis,
Semantics, Cameras, Lighting, Person re-identification,
bilinear pooling
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Sun, Y.F.[Yi-Fan],
Zheng, L.[Liang],
Li, Y.L.[Ya-Li],
Yang, Y.[Yi],
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Wang, S.J.[Sheng-Jin],
Learning Part-based Convolutional Features for Person
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PAMI(43), No. 3, March 2021, pp. 902-917.
IEEE DOI
2102
Pose estimation, Training, Feature extraction, Deep learning,
Semantics, Sun, Labeling, Person re-identification, part refinement
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Liu, C.[Cen],
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HLFNet: High-low Frequency Network for Person Re-Identification,
SPLetters(28), 2021, pp. 1140-1144.
IEEE DOI
2106
Feature extraction, Training, Data mining, Convolution,
Task analysis, Image color analysis, Cameras,
local and global feature
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Yu, X.T.[Xiao-Ting],
Guo, L.J.[Li-Jun],
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Self-Label Refining for Unsupervised Person Re-Identification,
SPLetters(29), 2022, pp. 1297-1301.
IEEE DOI
2206
Noise measurement, Training, Refining, Clustering algorithms,
Task analysis, Feature extraction, Robustness,
person re-identification
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Bai, Y.[Yan],
Wang, C.[Ce],
Lou, Y.H.[Yi-Hang],
Liu, J.[Jun],
Duan, L.Y.[Ling-Yu],
Hierarchical Connectivity-Centered Clustering for Unsupervised Domain
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IP(30), 2021, pp. 6715-6729.
IEEE DOI
2108
Feature extraction, Visualization, Training, Clustering methods,
Data mining, Adaptation models, Training data,
graph convolutional networks
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Bai, Y.[Yan],
Jiao, J.[Jile],
Ce, W.[Wang],
Liu, J.[Jun],
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Feng, X.T.[Xue-Tao],
Duan, L.Y.[Ling-Yu],
Person30K: A Dual-Meta Generalization Network for Person
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CVPR21(2123-2132)
IEEE DOI
2111
Training, Computational modeling,
Benchmark testing, Extraterrestrial measurements, Cameras, Data models
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Dai, Y.X.[Yong-Xing],
Sun, Y.F.[Yi-Fan],
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Bridging the Source-to-Target Gap for Cross-Domain Person
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IJCV(133), No. 1, January 2025, pp. 410-434.
Springer DOI
2501
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Rossi, L.[Luca],
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Pierdicca, R.[Roberto],
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Human trajectory prediction and generation using LSTM models and GANs,
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Elsevier DOI
2109
Trajectory generation, Trajectory prediction, LSTM, GANs
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Xie, J.Y.[Ji-Yang],
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Unsupervised person re-identification via simultaneous clustering and
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PR(126), 2022, pp. 108568.
Elsevier DOI
2204
Person re-identification, Domain adaptation,
Unsupervised clustering, Mask prediction, Semantic cluster
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Li, M.K.[Ming-Kun],
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Self-paced Bottom-up Clustering Network with Side Information for
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ICPR21(1430-1437)
IEEE DOI
2105
Training, Annealing, Convolution, Merging, Process control,
Benchmark testing, Cameras
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Lai, S.Q.[Shen-Qi],
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SPGNet: Serial and Parallel Group Network,
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IEEE DOI
2206
Convolution, Hardware, Task analysis,
Computational modeling, Feature extraction, Complexity theory,
person re-identification
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Bhuiyan, A.[Amran],
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STCA: Utilizing a spatio-temporal cross-attention network for
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Elsevier DOI
2206
Re-identification, Deep learning, 3D-CNNs, Cross attention
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Zhou, K.Y.[Kai-Yang],
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Cavallaro, A.[Andrea],
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Learning Generalisable Omni-Scale Representations for Person
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PAMI(44), No. 9, September 2022, pp. 5056-5069.
IEEE DOI
2208
BibRef
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Omni-Scale Feature Learning for Person Re-Identification,
ICCV19(3701-3711)
IEEE DOI
2004
Code, Re-Identification.
WWW Link. Adaptation models, Convolutional codes, Architecture, Cameras,
Feature extraction, Data models, Convolution,
neural architecture search.
convolutional neural nets, graph theory,
image representation, learning (artificial intelligence), Convolution
BibRef
Wang, X.D.[Xiao-Dong],
Zheng, Z.[Zhedong],
He, Y.[Yang],
Yan, F.[Fei],
Zeng, Z.Q.[Zhi-Qiang],
Yang, Y.[Yi],
Soft Person Reidentification Network Pruning via Blockwise Adjacent
Filter Decaying,
Cyber(52), No. 12, December 2022, pp. 13293-13307.
IEEE DOI
2212
Redundancy, Feature extraction, Training, Neural networks,
Convolutional neural networks, Deep learning, representation learning
BibRef
Pan, X.[Xiao],
Luo, H.[Hao],
Chen, W.H.[Wei-Hua],
Wang, F.[Fan],
Li, H.[Hao],
Jiang, W.[Wei],
Zhang, J.M.[Jian-Ming],
Gu, J.Y.[Jian-Yang],
Li, P.[Peike],
Dynamic gradient reactivation for backward compatible person
re-identification,
PR(146), 2024, pp. 110000.
Elsevier DOI
2311
Person re-identification, Backward compatible training, Deep learning
BibRef
Chen, S.[Si],
Da, H.[Hui],
Wang, D.H.[Da-Han],
Zhang, X.Y.[Xu-Yao],
Yan, Y.[Yan],
Zhu, S.Z.[Shun-Zhi],
HASI: Hierarchical Attention-Aware Spatio-Temporal Interaction for
Video-Based Person Re-Identification,
CirSysVideo(34), No. 6, June 2024, pp. 4973-4988.
IEEE DOI
2406
Feature extraction, Transformers, Pedestrians,
Convolutional neural networks, Semantics, Silicon, deep feature fusion
BibRef
Lv, Y.[Yuanhai],
Wang, G.[Gexuan],
Zhao, W.Q.[Wan-Qing],
Zhao, W.[Wei],
Guan, Z.Y.[Zi-Yu],
Edge-Weight-Embedding Graph Convolutional Network for Person
Reidentification,
IEEE_Int_Sys(39), No. 4, July 2024, pp. 74-82.
IEEE DOI
2408
Feature extraction, Convolutional neural networks, Robustness,
Intelligent systems, Identification of persons, Skeleton
BibRef
Matsukawa, T.[Tetsu],
Suzuki, E.[Einoshin],
Convolutional Feature Transfer via Camera-Specific Discriminative
Pooling for Person Re-Identification,
ICPR21(8408-8415)
IEEE DOI
2105
Training, Legged locomotion, Cameras, Spatial databases,
Security, Convolutional neural networks
BibRef
Breckon, T.P.[Toby P.],
Alsehaim, A.[Aishah],
Not 3D Re-ID:
Simple Single Stream 2D Convolution for Robust Video Re-identification,
ICPR21(5190-5197)
IEEE DOI
2105
Training, Solid modeling, Convolution,
Surveillance, Transfer learning, Streaming media
BibRef
Zhang, L.[Lei],
Jiang, N.[Na],
Xu, Y.[Yue],
Diao, Q.S.[Qi-Shuai],
Zhou, Z.[Zhong],
Wu, W.[Wei],
Pose Variation Adaptation for Person Re-identification,
ICPR21(6996-7003)
IEEE DOI
2105
Training, Deep learning, Adaptation models, Image synthesis,
Surveillance, Shape measurement, Feature extraction
BibRef
Hong, P.X.[Pei-Xian],
Wu, A.C.[An-Cong],
Zheng, W.S.[Wei-Shi],
Semi-supervised Person Re-identification by Attribute Similarity
Guidance,
ICPR21(6471-6477)
IEEE DOI
2105
Training, Deep learning, Annotations, Semantics,
Semisupervised learning, Cameras
BibRef
Chen, C.[Chen],
Dou, H.[Hao],
Hu, X.[Xiyuan],
Peng, S.[Silong],
Deep Top-rank Counter Metric for Person Re-identification,
ICPR21(2732-2739)
IEEE DOI
2105
Measurement, Deep learning, Training, Learning systems, Boosting,
Usability, person re-identification,
deep learning
BibRef
Wang, C.H.[Chang-Hao],
Zhou, J.[Jun],
Duan, X.F.[Xian-Fei],
Zhang, G.[Guanwen],
Zhou, W.[Wei],
Recurrent Deep Attention Network for Person Re-Identification,
ICPR21(4276-4281)
IEEE DOI
2105
Visualization, Reinforcement learning, Benchmark testing,
Video surveillance, Cameras, Concrete, Cognition
BibRef
Lin, C.,
Guo, R.,
Li, M.,
Qi, X.,
Li, C.G.,
Learning Convolution Feature Aggregation via Edge Attention
Convolution Network for Person Re-Identification,
VCIP20(539-542)
IEEE DOI
2102
Convolution, Image edge detection, Feature extraction, Measurement,
Entropy, Smoothing methods, Training, Person ReID, Over-smoothing
BibRef
Mohamed, A.,
Qian, K.,
Elhoseiny, M.,
Claudel, C.,
Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural
Network for Human Trajectory Prediction,
CVPR20(14412-14420)
IEEE DOI
2008
Trajectory, Predictive models, Convolution, Kernel,
Convolutional neural networks, Autonomous vehicles, Data models
BibRef
Subramaniam, A.,
Nambiar, A.,
Mittal, A.,
Co-Segmentation Inspired Attention Networks for Video-Based Person
Re-Identification,
ICCV19(562-572)
IEEE DOI
2004
feature extraction, image segmentation, object detection,
video signal processing, video surveillance, video-based person,
Convolution
BibRef
Liu, Z.,
Wang, J.,
Gong, S.,
Tao, D.,
Lu, H.,
Deep Reinforcement Active Learning for Human-in-the-Loop Person
Re-Identification,
ICCV19(6121-6130)
IEEE DOI
2004
convolutional neural nets, image annotation,
learning (artificial intelligence), Computational modeling
BibRef
Quan, R.,
Dong, X.,
Wu, Y.,
Zhu, L.,
Yang, Y.,
Auto-ReID: Searching for a Part-Aware ConvNet for Person
Re-Identification,
ICCV19(3749-3758)
IEEE DOI
2004
convolutional neural nets, image classification,
part-aware ConvNet, person re-identification,
Search problems
BibRef
Dai, Z.,
Chen, M.,
Gu, X.,
Zhu, S.,
Tan, P.,
Batch DropBlock Network for Person Re-Identification and Beyond,
ICCV19(3690-3700)
IEEE DOI
2004
convolutional neural nets, feature extraction,
learning (artificial intelligence), Cameras
BibRef
Zhu, Y.,
Guo, X.,
Liu, J.,
Jiang, Z.,
Multi-Branch Context-Aware Network for Person Re-Identification,
ICIP19(2274-2278)
IEEE DOI
1910
Person re-identification, convolutional neural networks,
contextual dependencies, attention module
BibRef
Xin, X.,
Wu, X.,
Wang, Y.,
Wang, J.,
Deep Self-Paced Learning for Semi-Supervised Person Re-Identification
Using Multi-View Self-Paced Clustering,
ICIP19(2631-2635)
IEEE DOI
1910
Person Re-Identification, Semi-Supervised Learning,
Convolutional Neural Network, Multi-View Clustering, Self-paced Learning
BibRef
Sun, X.,
Zhang, N.,
Chen, Q.,
Cao, Y.,
Liu, B.,
People Re-Identification by Multi-Branch CNN with Multi-Scale
Features,
ICIP19(2269-2273)
IEEE DOI
1910
People re-identification, Multi-branch CNN, Multi-scale features, Triplet loss
BibRef
Yin, J.,
Li, B.,
Wan, F.,
Zhu, Y.,
A New Data Selection Strategy for One-Shot Video-Based Person
Re-Identification,
ICIP19(1227-1231)
IEEE DOI
1910
Person re-identification, one-shot, semi-supervised, deep learning
BibRef
Ponce-López, V.[Víctor],
Burghardt, T.[Tilo],
Hannunna, S.[Sion],
Damen, D.[Dima],
Masullo, A.[Alessandro],
Mirmehdi, M.[Majid],
Semantically Selective Augmentation for Deep Compact Person
Re-Identification,
PersonContext18(II:551-561).
Springer DOI
1905
BibRef
Li, Y.,
Yang, F.,
Liu, Y.,
Yeh, Y.,
Du, X.,
Wang, Y.F.,
Adaptation and Re-identification Network: An Unsupervised Deep
Transfer Learning Approach to Person Re-identification,
Crowd18(285-2856)
IEEE DOI
1812
Adaptation models, Training, Cameras, Task analysis, Data models,
Visualization, Feature extraction
BibRef
Chen, D.,
Xu, D.,
Li, H.,
Sebe, N.,
Wang, X.,
Group Consistent Similarity Learning via Deep CRF for Person
Re-identification,
CVPR18(8649-8658)
IEEE DOI
1812
Training, Measurement, Probes, Neural networks, Estimation,
Graphical models, Task analysis
BibRef
Shen, Y.,
Xiao, T.,
Li, H.,
Yi, S.,
Wang, X.,
End-to-End Deep Kronecker-Product Matching for Person
Re-identification,
CVPR18(6886-6895)
IEEE DOI
1812
Estimation, Neural networks, Measurement, Layout, Semantics
BibRef
Chen, D.P.[Da-Peng],
Li, H.S.[Hong-Sheng],
Liu, X.H.[Xi-Hui],
Shen, Y.T.[Yan-Tao],
Shao, J.[Jing],
Yuan, Z.J.[Ze-Jian],
Wang, X.G.[Xiao-Gang],
Improving Deep Visual Representation for Person Re-identification by
Global and Local Image-language Association,
ECCV18(XVI: 56-73).
Springer DOI
1810
BibRef
Jiao, F.,
Bhanu, B.,
Deepagent: An Algorithm Integration Approach for Person
Re-Identification,
ICIP18(853-857)
IEEE DOI
1809
Probes, Feature extraction, Training, Cameras,
Learning (artificial intelligence), Neural networks, Testing,
Algorithm integration
BibRef
Chen, W.,
Chen, X.,
Zhang, J.,
Huang, K.,
Beyond Triplet Loss:
A Deep Quadruplet Network for Person Re-identification,
CVPR17(1320-1329)
IEEE DOI
1711
Feature extraction, Loss measurement, Machine learning, Probes,
Testing, Training
BibRef
Marchwica, P.,
Jamieson, M.,
Siva, P.,
An Evaluation of Deep CNN Baselines for Scene-Independent Person
Re-identification,
CRV18(297-304)
IEEE DOI
1812
Cameras, Training, Buildings, Network architecture, Testing,
Training data, Airports, Person Re-identification, Deep Learning
BibRef
Zhao, Y.,
Luo, S.,
Yang, Y.,
Song, M.,
DeepSSH: Deep Semantic Structured Hashing for Explainable Person
Re-Identification,
ICIP18(1653-1657)
IEEE DOI
1809
CNN, person re-identification, hashing
BibRef
Yu, J.,
Ko, D.,
Moon, H.,
Jeon, M.,
Deep Discriminative Representation Learning for Face Verification and
Person Re-Identification on Unconstrained Condition,
ICIP18(1658-1662)
IEEE DOI
1809
Task analysis, Face, Feature extraction, Measurement, Training,
Optimization, Probes, person re-identification
BibRef
Zhang, Y.H.[Yong-Hui],
Shao, J.[Jie],
Ouyang, D.Q.[De-Qiang],
Shen, H.T.[Heng Tao],
Person Re-identification Using Two-Stage Convolutional Neural Network,
ICPR18(3341-3346)
IEEE DOI
1812
Feature extraction, Image sequences,
Convolutional neural networks, Computer aided instruction,
Training
BibRef
Xiang, J.,
Lin, R.,
Hou, J.,
Huang, W.,
Person Re-identification Based on Feature Fusion and Triplet Loss
Function,
ICPR18(3477-3482)
IEEE DOI
1812
Feature extraction, Semantics, Measurement, Task analysis,
Neural networks, Convolution, Training
BibRef
Du, P.,
Song, Y.,
Zhang, Y.,
Which Part is Better: Multi-Part Competition Network for person
Re-Identification,
ICPR18(1634-1639)
IEEE DOI
1812
Feature extraction, Head, Detectors, Measurement, Convolution,
Magnetic heads, Legged locomotion, person re-identification,
Multi-Part Competition Network
BibRef
Guo, Y.,
Cheung, N.,
Efficient and Deep Person Re-identification Using Multi-level
Similarity,
CVPR18(2335-2344)
IEEE DOI
1812
Feature extraction, Convolution, Visualization, Task analysis,
Measurement, Image color analysis, Computational modeling
BibRef
Chen, Y.Q.[Yi-Qiang],
Duffner, S.[Stefan],
Stoian, A.[Andrei],
Dufour, J.Y.[Jean-Yves],
Baskurt, A.[Atilla],
Person Re-identification Using Group Context,
ACIVS18(392-401).
Springer DOI
1810
BibRef
And:
Person Re-Identification with a Body Orientation-Specific Convolutional
Neural Network,
ACIVS18(26-37).
Springer DOI
1810
BibRef
And: A1, A2, A5, A3, A4:
Similarity Learning with Listwise Ranking for Person
Re-Identification,
ICIP18(843-847)
IEEE DOI
1809
Training, Loss measurement, Probes, Robustness, Machine learning,
Manganese, Video surveillance,
Similarity learning
BibRef
Liu, J.,
Yang, Z.,
Zhang, T.,
Xiong, H.,
Multi-part compact bilinear CNN for person re-identification,
ICIP17(2309-2313)
IEEE DOI
1803
Convolution, Convolutional neural networks, Feature extraction,
Histograms, Machine learning, Measurement, Task analysis,
multi-part
BibRef
Kim, J.,
Yoo, C.D.,
Deep partial person re-identification via attention model,
ICIP17(3425-3429)
IEEE DOI
1803
Convolution, Feature extraction, Kernel, Measurement,
Neural networks, Probes, Training, Attention model,
RoI Pooling
BibRef
Chung, D.,
Tahboub, K.,
Delp, E.J.,
A Two Stream Siamese Convolutional Neural Network for Person
Re-identification,
ICCV17(1992-2000)
IEEE DOI
1802
convolution, image matching, neural nets, video surveillance,
matching accuracy, person re-identification,
Streaming media
BibRef
Chen, Y.,
Duffner, S.,
Stoian, A.,
Dufour, J.Y.,
Baskurt, A.,
Triplet CNN and pedestrian attribute recognition for improved person
re-identification,
AVSS17(1-6)
IEEE DOI
1806
feature extraction, image representation,
learning (artificial intelligence), multilayer perceptrons,
Visualization
BibRef
Rahimpour, A.,
Liu, L.,
Taalimi, A.,
Song, Y.,
Qi, H.,
Person re-identification using visual attention,
ICIP17(4242-4246)
IEEE DOI
1803
Computational modeling, Measurement,
Neural networks, Task analysis, Training, Visualization, Deep CNN,
Triplet loss
BibRef
Carr, S.B.P.,
Deep spatial pyramid for person re-identification,
AVSS17(1-6)
IEEE DOI
1806
cellular neural nets, feature extraction, image classification,
image representation, image sensors,
Training
BibRef
Zhang, Y.H.[Yi-Hao],
Wang, W.M.[Wen-Min],
Wang, J.Z.[Jin-Zhuo],
Deep discriminative network with inception module for person
re-identification,
VCIP17(1-4)
IEEE DOI
1804
cameras, feature extraction,
feedforward neural nets, image classification, image matching,
person re-identification
BibRef
Lin, S.,
Li, C.T.,
End-to-End Correspondence and Relationship Learning of Mid-Level Deep
Features for Person Re-Identification,
DICTA17(1-6)
IEEE DOI
1804
feature extraction, image matching, image representation,
learning (artificial intelligence), neural nets,
Training
BibRef
Zhao, L.,
Li, X.,
Zhuang, Y.,
Wang, J.,
Deeply-Learned Part-Aligned Representations for Person
Re-identification,
ICCV17(3239-3248)
IEEE DOI
1802
image matching, image representation,
learning (artificial intelligence), neural nets, Probes
BibRef
Zhou, S.,
Wang, J.,
Wang, J.,
Gong, Y.,
Zheng, N.,
Point to Set Similarity Based Deep Feature Learning for Person
Re-Identification,
CVPR17(5028-5037)
IEEE DOI
1711
Cameras, Feature extraction, Learning systems, Lighting,
Machine learning, Measurement, Robustness
BibRef
Li, D.,
Chen, X.,
Zhang, Z.,
Huang, K.,
Learning Deep Context-Aware Features over Body and Latent Parts for
Person Re-identification,
CVPR17(7398-7407)
IEEE DOI
1711
Clutter, Feature extraction, Image color analysis, Kernel,
Machine learning, Visualization
BibRef
Zhang, L.[Li],
Xiang, T.[Tao],
Gong, S.G.[Shao-Gang],
Learning a Deep Embedding Model for Zero-Shot Learning,
CVPR17(3010-3019)
IEEE DOI
1711
BibRef
Earlier:
Learning a Discriminative Null Space for Person Re-identification,
CVPR16(1239-1248)
IEEE DOI
1612
Computational modeling, Neural networks, Prototypes,
Search problems, Semantics, Training, Visualization
BibRef
Varior, R.R.[Rahul Rama],
Haloi, M.[Mrinal],
Wang, G.[Gang],
Gated Siamese Convolutional Neural Network Architecture for Human
Re-identification,
ECCV16(VIII: 791-808).
Springer DOI
1611
BibRef
Wu, S.,
Chen, Y.C.,
Li, X.,
Wu, A.C.,
You, J.J.,
Zheng, W.S.,
An enhanced deep feature representation for person re-identification,
WACV16(1-8)
IEEE DOI
1606
Convolution
BibRef
Ahmed, E.[Ejaz],
Jones, M.[Michael],
Marks, T.K.[Tim K.],
An improved deep learning architecture for person re-identification,
CVPR15(3908-3916)
IEEE DOI
1510
BibRef
Schumann, A.,
Stiefelhagen, R.[Rainer],
Person Re-identification by Deep Learning Attribute-Complementary
Information,
Re-Id17(1435-1443)
IEEE DOI
1709
Cameras, Machine learning, Robustness, Semantics, Training, Training, data
BibRef
Schumann, A.,
Bauml, M.[Martin],
Stiefelhagen, R.[Rainer],
Person tracking-by-detection with efficient selection of
part-detectors,
AVSS13(43-50)
IEEE DOI
1311
computer graphics
BibRef
Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Adversarial Learning, GAN, Re-Identification Issues, Pedestrian Tracking .