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IEEE DOI
1112
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Zhou, Y.,
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IP(27), No. 7, July 2018, pp. 3275-3287.
IEEE DOI
1805
automobiles, computer vision, convolution, feedforward neural nets,
image representation, inference mechanisms,
spatially concatenated ConvNet
BibRef
Zhou, Y.,
Shao, L.,
Viewpoint-Aware Attentive Multi-view Inference for Vehicle
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CVPR18(6489-6498)
IEEE DOI
1812
BibRef
Earlier:
Vehicle Re-Identification by Adversarial Bi-Directional LSTM Network,
WACV18(653-662)
IEEE DOI
1806
Feature extraction, Visualization, Training,
Extraterrestrial measurements, Image color analysis, Task analysis.
image representation,
intelligent transportation systems, object detection,
Visualization
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Liu, X.C.[Xin-Chen],
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IEEE DOI
1802
BibRef
Earlier:
A Deep Learning-Based Approach to Progressive Vehicle Re-identification
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ECCV16(II: 869-884).
Springer DOI
1611
Cameras, Image color analysis, Licenses, Multimedia communication,
Spatiotemporal phenomena, Video surveillance, Progressive search,
vehicle re-identification
BibRef
Bashir, R.M.S.[Raja Muhammad Saad],
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PR(90), 2019, pp. 52-65.
Elsevier DOI
1903
BibRef
Earlier:
DUPL-VR: Deep Unsupervised Progressive Learning for Vehicle
Re-Identification,
ISVC18(286-295).
Springer DOI
1811
Vehicle re-id, Deep learning, Unsupervised, Clustering,
Visual surveillance, Progressive learning, Self pace
BibRef
Khan, S.D.[Sultan Daud],
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A survey of advances in vision-based vehicle re-identification,
CVIU(182), 2019, pp. 50-63.
Elsevier DOI
1905
Survey, Vehicle Re-Identification. Re-identification, Hand-crafted methods,
Convolutional neural network, Traffic analysis
BibRef
Wu, F.Y.[Fang-Yu],
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SP:IC(76), 2019, pp. 261-271.
Elsevier DOI
1906
Vehicle re-identification, Convolutional neural networks,
Semi-supervised learning, Re-ranking
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Lou, Y.,
Bai, Y.,
Liu, J.,
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Duan, L.,
Embedding Adversarial Learning for Vehicle Re-Identification,
IP(28), No. 8, August 2019, pp. 3794-3807.
IEEE DOI
1907
embedded systems, image sampling,
learning (artificial intelligence), cross-view generation,
cross-view
BibRef
Guo, H.,
Zhu, K.,
Tang, M.,
Wang, J.,
Two-Level Attention Network With Multi-Grain Ranking Loss for Vehicle
Re-Identification,
IP(28), No. 9, Sep. 2019, pp. 4328-4338.
IEEE DOI
1908
cameras, feature extraction, learning (artificial intelligence),
object recognition, traffic engineering computing,
feature embedding
BibRef
Ooi, H.L.[Hui-Lee],
Bilodeau, G.A.[Guillaume-Alexandre],
Saunier, N.[Nicolas],
Tracking in Urban Traffic Scenes from Background Subtraction and Object
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ICIAR19(I:195-206).
Springer DOI
1909
BibRef
Kan, S.C.[Shi-Chao],
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He, Z.H.[Zhi-Hai],
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Supervised Deep Feature Embedding With Handcrafted Feature,
IP(28), No. 12, December 2019, pp. 5809-5823.
IEEE DOI
1909
Measurement, Image retrieval, Feature extraction, Fuses,
Task analysis, Training, Neural networks, Deep feature embedding,
vehicle re-identification
BibRef
Liu, X.,
Zhang, S.,
Wang, X.,
Hong, R.,
Tian, Q.,
Group-Group Loss-Based Global-Regional Feature Learning for Vehicle
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IP(29), 2020, pp. 2638-2652.
IEEE DOI
2001
Vehicle re-identification, CNN, global-regional feature learning,
distance metric learning
BibRef
Zhu, J.,
Zeng, H.,
Huang, J.,
Liao, S.,
Lei, Z.,
Cai, C.,
Zheng, L.,
Vehicle Re-Identification Using Quadruple Directional Deep Learning
Features,
ITS(21), No. 1, January 2020, pp. 410-420.
IEEE DOI
2001
Deep learning, Feature extraction, Convolutional neural networks,
Databases, Measurement, Cameras,
image classification
BibRef
Zhao, Y.,
Shen, C.,
Wang, H.,
Chen, S.,
Structural Analysis of Attributes for Vehicle Re-Identification and
Retrieval,
ITS(21), No. 2, February 2020, pp. 723-734.
IEEE DOI
2002
Feature extraction, Automobiles, Task analysis, Licenses, Cameras,
Proposals, Surveillance, Vehicle attribute detection,
vehicle retrieval
BibRef
Španhel, J.[Jakub],
Sochor, J.[Jakub],
Juránek, R.[Roman],
Dobeš, P.[Petr],
Bartl, V.[Vojtech],
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Learning feature aggregation in temporal domain for re-identification,
CVIU(192), 2020, pp. 102883.
Elsevier DOI
2002
BibRef
Zapletal, D.,
Herout, A.,
Vehicle Re-identification for Automatic Video Traffic Surveillance,
Traffic16(1568-1574)
IEEE DOI
1612
BibRef
Khorramshahi, P.,
Kumar, A.,
Peri, N.,
Rambhatla, S.S.,
Chen, J.,
Chellappa, R.,
A Dual-Path Model With Adaptive Attention for Vehicle
Re-Identification,
ICCV19(6131-6140)
IEEE DOI
2004
Code, Re-Identification.
WWW Link. feature extraction, learning (artificial intelligence),
vehicle re-identification, attention models, Task analysis
BibRef
Wang, P.,
Jiao, B.,
Yang, L.,
Yang, Y.,
Zhang, S.,
Wei, W.,
Zhang, Y.,
Vehicle Re-Identification in Aerial Imagery: Dataset and Approach,
ICCV19(460-469)
IEEE DOI
2004
image processing, traffic engineering computing, aerial imagery,
UAV-mounted cameras, UAV-based vehicle ReID dataset,
Visualization
BibRef
Tang, Z.,
Naphade, M.,
Birchfield, S.,
Tremblay, J.,
Hodge, W.,
Kumar, R.,
Wang, S.,
Yang, X.,
PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification
Using Highly Randomized Synthetic Data,
ICCV19(211-220)
IEEE DOI
2004
feature extraction, image classification, image representation,
image segmentation, learning (artificial intelligence), Solid modeling
BibRef
Wu, M.J.[Ming-Jie],
Zhang, Y.F.[Yong-Fei],
Zhang, T.Y.[Tian-Yu],
Zhang, W.Q.[Wen-Qi],
Background Segmentation for Vehicle Re-identification,
MMMod20(II:88-99).
Springer DOI
2003
BibRef
Lou, Y.H.[Yi-Hang],
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Wang, S.[Shiqi],
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VERI-Wild: A Large Dataset and a New Method for Vehicle
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CVPR19(3230-3238).
IEEE DOI
2002
BibRef
He, B.[Bing],
Li, J.[Jia],
Zhao, Y.[Yifan],
Tian, Y.H.[Yong-Hong],
Part-Regularized Near-Duplicate Vehicle Re-Identification,
CVPR19(3992-4000).
IEEE DOI
2002
BibRef
Yang, X.,
Lang, C.,
Peng, P.,
Xing, J.,
Vehicle Re-Identification by Multi-Grain Learni,
ICIP19(3113-3117)
IEEE DOI
1910
Vehicle re-identification, Multi-grain ranking loss
BibRef
Alfasly, S.A.S.,
Hu, Y.,
Liang, T.,
Jin, X.,
Zhao, Q.,
Liu, B.,
Variational Representation Learning for Vehicle Re-Identificati,
ICIP19(3118-3122)
IEEE DOI
1910
Deep Learning, LSTM, Variational Features, Vehicle Re-Identification
BibRef
de Oliveira, I.O.,
Fonseca, K.V.O.,
Minetto, R.,
A Two-Stream Siamese Neural Network for Vehicle Re-Identification by
Using Non-Overlapping Cameras,
ICIP19(669-673)
IEEE DOI
1910
Vehicle Re-identification, Siamese Neural Networks,
Vehicle Matching, Travel Time Estimation
BibRef
Wei, X.S.[Xiu-Shen],
Zhang, C.L.[Chen-Lin],
Liu, L.Q.[Ling-Qiao],
Shen, C.H.[Chun-Hua],
Wu, J.X.[Jian-Xin],
Coarse-to-Fine: A RNN-Based Hierarchical Attention Model for Vehicle
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ACCV18(II:575-591).
Springer DOI
1906
BibRef
Zhong, X.[Xian],
Feng, M.[Meng],
Huang, W.X.[Wen-Xin],
Wang, Z.[Zheng],
Satoh, S.[Shin'Ichi],
Poses Guide Spatiotemporal Model for Vehicle Re-identification,
MMMod19(II:426-439).
Springer DOI
1901
BibRef
Wu, F.,
Yan, S.,
Smith, J.S.,
Zhang, B.,
Joint Semi-supervised Learning and Re-ranking for Vehicle
Re-identification,
ICPR18(278-283)
IEEE DOI
1812
Training, Probes, Feature extraction, Semisupervised learning,
Generative adversarial networks, Smoothing methods, Cameras
BibRef
Marín-Reyes, P.A.,
Bergamini, L.[Luca],
Lorenzo-Navarro, J.,
Palazzi, A.[Andrea],
Calderara, S.[Simone],
Cucchiara, R.[Rita],
Unsupervised Vehicle Re-identification Using Triplet Networks,
City18(166-1665)
IEEE DOI
1812
Videos, Urban areas, Task analysis, Artificial intelligence,
Detectors, Surveillance, Cameras
BibRef
Li, S.,
Pei, M.,
Zhu, L.,
Vehicle Re-Identification by Deep Feature Fusion Based on Joint
Bayesian Criterion,
ICPR18(2032-2037)
IEEE DOI
1812
Feature extraction, Bayes methods, Fuses, Licenses, Training,
Training data, Task analysis
BibRef
Zhu, J.,
Zeng, H.,
Lei, Z.,
Liao, S.,
Zheng, L.,
Cai, C.,
A Shortly and Densely Connected Convolutional Neural Network for
Vehicle Re-identification,
ICPR18(3285-3290)
IEEE DOI
1812
Convolutional neural networks, Linear programming,
Feature extraction, Training, Cameras, Surveillance
BibRef
Wu, C.,
Liu, C.,
Chiang, C.,
Tu, W.,
Chien, S.,
Vehicle Re-identification with the Space-Time Prior,
City18(121-1217)
IEEE DOI
1812
Feature extraction, Videos, Automobiles, Task analysis, Urban areas,
Visualization, Testing
BibRef
Jiang, N.,
Xu, Y.,
Zhou, Z.,
Wu, W.,
Multi-Attribute Driven Vehicle Re-Identification with
Spatial-Temporal Re-Ranking,
ICIP18(858-862)
IEEE DOI
1809
Feature extraction, Image color analysis, Computer architecture,
Machine learning, Probes, Lighting, Cameras,
spatial-temporal re-ranking
BibRef
Kanaci, A.[Aytaç],
Zhu, X.T.[Xia-Tian],
Gong, S.G.[Shao-Gang],
Vehicle Re-identification in Context,
GCPR18(377-390).
Springer DOI
1905
BibRef
Cui, C.,
Sang, N.,
Gao, C.,
Zou, L.,
Vehicle re-identification by fusing multiple deep neural networks,
IPTA17(1-6)
IEEE DOI
1804
convolution, feature extraction, feedforward neural nets,
image classification, image colour analysis, image fusion,
Vehicle re-identification
BibRef
Tang, Y.,
Wu, D.,
Jin, Z.,
Zou, W.,
Li, X.,
Multi-modal metric learning for vehicle re-identification in traffic
surveillance environment,
ICIP17(2254-2258)
IEEE DOI
1803
Cameras, Feature extraction, Image color analysis, Measurement,
Robustness, Surveillance, Training, Convolutional Neural Network,
Vehicle Re-identification
BibRef
Li, Y.Q.[Yu-Qi],
Li, Y.H.[Yang-Hao],
Yan, H.F.[Hong-Fei],
Liu, J.Y.[Jia-Ying],
Deep joint discriminative learning for vehicle re-identification and
retrieval,
ICIP17(395-399)
IEEE DOI
1803
Computational modeling, Face recognition, Feature extraction,
Image recognition, Machine learning, Task analysis, Training,
Vehicle Retrieval
BibRef
Shen, Y.,
Xiao, T.,
Li, H.,
Yi, S.,
Wang, X.,
Learning Deep Neural Networks for Vehicle Re-ID with
Visual-spatio-Temporal Path Proposals,
ICCV17(1918-1927)
IEEE DOI
1802
computer vision, feature extraction, image retrieval,
intelligent transportation systems,
Visualization
BibRef
Wang, Z.,
Tang, L.,
Liu, X.,
Yao, Z.,
Yi, S.,
Shao, J.,
Yan, J.,
Wang, S.,
Li, H.,
Wang, X.,
Orientation Invariant Feature Embedding and Spatial Temporal
Regularization for Vehicle Re-identification,
ICCV17(379-387)
IEEE DOI
1802
feature extraction, image retrieval, spatiotemporal phenomena,
traffic engineering computing, feature extraction,
Wheels
BibRef
Cormier, M.,
Sommer, L.W.,
Teutsch, M.,
Low resolution vehicle re-identification based on appearance features
for wide area motion imagery,
CVAST16(1-7)
IEEE DOI
1606
image colour analysis
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Vehicle Tracking, Speed Computations, Vehicle Speed, Traffic Speed .