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automobiles, computer vision, convolution, feedforward neural nets,
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Vehicle Re-Identification by Adversarial Bi-Directional LSTM Network,
WACV18(653-662)
IEEE DOI
1806
Feature extraction, Visualization, Training,
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A Deep Learning-Based Approach to Progressive Vehicle Re-identification
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1611
Cameras, Image color analysis, Licenses, Multimedia communication,
Spatiotemporal phenomena, Video surveillance, Progressive search,
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1811
Vehicle re-id, Deep learning, Unsupervised, Clustering,
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Survey, Vehicle Re-Identification. Re-identification, Hand-crafted methods,
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Vehicle re-identification, Convolutional neural networks,
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1907
embedded systems, image sampling,
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1908
cameras, feature extraction, learning (artificial intelligence),
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1909
Measurement, Image retrieval, Feature extraction, Fuses,
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2001
Vehicle re-identification, CNN, global-regional feature learning,
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Cai, C.,
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Vehicle Re-Identification Using Quadruple Directional Deep Learning
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IEEE DOI
2001
Deep learning, Feature extraction, Convolutional neural networks,
Databases, Measurement, Cameras,
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Structural Analysis of Attributes for Vehicle Re-Identification and
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2002
Feature extraction, Automobiles, Task analysis, Licenses, Cameras,
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Vehicle Re-identification for Automatic Video Traffic Surveillance,
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Vehicle re-identification, Keypoint detection, Multi-branch network
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Elsevier DOI
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Vehicle re-identification, Unsupervised,
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Wang, H.,
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2012
Task analysis, Image color analysis, Training, Feature extraction,
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Vehicle Re-Identification Using Distance-Based Global and Partial
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2102
Spatiotemporal phenomena, Visualization, Cameras,
Feature extraction, Interference, vehicle re-identification
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Multi-View Spatial Attention Embedding for Vehicle Re-Identification,
CirSysVideo(31), No. 2, February 2021, pp. 816-827.
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2102
Feature extraction, Task analysis, Measurement, Visualization,
Computer science, Training, Neural networks,
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Model Latent Views with Multi-Center Metric Learning for Vehicle
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ITS(22), No. 3, March 2021, pp. 1919-1931.
IEEE DOI
2103
Feature extraction, Visualization, Training, Measurement,
Annotations, Task analysis, Semantics, Multi-view modeling,
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2106
Cameras, Trajectory, Target tracking, Task analysis, Metadata,
Feature extraction, Image color analysis, MTMCT,
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Roman-Jimenez, G.[Geoffrey],
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2107
Deep learning, vehicle make and model recognition,
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2109
Training, Robustness, Adaptation models, Data models, Automobiles,
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City20(2550-2558)
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Training, Visualization, Robustness, Feature extraction,
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Vehicle re-identification, Hierarchical attention network, Multi-views
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2109
Feature extraction, Semantics, Automotive components,
Visualization, Video surveillance, Licenses, Vehicular ad hoc networks
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AICity21(4098-4106)
IEEE DOI
2109
Measurement, Filtering, Smart cities, Visual analytics,
Vehicle detection, Pipelines, Streaming media
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A Multi-Camera Vehicle Tracking System based on City-Scale Vehicle
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AICity21(4072-4081)
IEEE DOI
2109
Visualization, Uncertainty, Urban areas, Lighting,
Feature extraction, Robustness, Data models
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Yang, K.S.[Kai-Siang],
Chen, Y.K.[Yu-Kai],
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Tracklet-refined Multi-Camera Tracking based on Balanced Cross-Domain
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AICity21(3978-3987)
IEEE DOI
2109
Training, Target tracking, Training data,
Filtering algorithms, Information filters, Data models
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Jiang, M.[Minyue],
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Bai, Z.[Zechen],
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Yang, Y.[Yi],
Robust Vehicle Re-identification via Rigid Structure Prior,
AICity21(4021-4028)
IEEE DOI
2109
Geometry, Visualization, Matched filters, Scalability, Urban areas,
Lighting, Feature extraction
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Luo, H.[Hao],
Chen, W.H.[Wei-Hua],
Xu, X.[Xianzhe],
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Jiang, Y.[Yiqi],
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Li, H.[Hao],
An Empirical Study of Vehicle Re-Identification on the AI City
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AICity21(4090-4097)
IEEE DOI
2109
Training, Computational modeling,
Urban areas, Training data, Data models
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Huynh, S.V.[Su V.],
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A Strong Baseline for Vehicle Re-Identification,
AICity21(4142-4149)
IEEE DOI
2109
Training, Target tracking, Head, Urban areas, Stacking
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Sun, Y.L.[Yong-Li],
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Wei, H.[Hua],
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Tian, J.[Jiahao],
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Progressive Data Mining and Adaptive Weighted Multi-Model Ensemble
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AICity21(4196-4201)
IEEE DOI
2109
Training, Adaptation models, Computational modeling,
Image matching, Urban areas, Lighting, Data models
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Multi-level Deep Learning Vehicle Re-identification using
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ICPR21(9099-9106)
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2105
Measurement, Space vehicles, Deep learning, Annotations,
System performance, Cameras, Pattern recognition
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Learning Matching Behavior Differences for Compressing Vehicle
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VCIP20(523-526)
IEEE DOI
2102
Training, Testing, Probes, Image coding, Loss measurement,
Computational modeling, Trajectory, Deep Learning,
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Lee, S.,
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StRDAN: Synthetic-to-Real Domain Adaptation Network for Vehicle
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City20(2590-2597)
IEEE DOI
2008
Adaptation models, Feature extraction, Task analysis, Training,
Data models, Image color analysis, Urban areas
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Meng, D.,
Li, L.,
Liu, X.,
Li, Y.,
Yang, S.,
Zha, Z.,
Gao, X.,
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CVPR20(7101-7110)
IEEE DOI
2008
Feature extraction, Task analysis, Cameras,
Training, Image color analysis, Fuses
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Chen, T.,
Lee, M.,
Liu, C.,
Chien, S.,
Viewpoint-aware Channel-wise Attentive Network for Vehicle
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City20(2448-2455)
IEEE DOI
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Feature extraction, Estimation, Cameras, Task analysis, Semantics,
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Vehicle Re-Identification based on Ensembling Deep Learning Features
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AICity21(4063-4071)
IEEE DOI
2109
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Earlier: A2, A3, A4, Only:
Vehicle Re-Identification in Multi-Camera scenarios based on
Ensembling Deep Learning Features,
City20(2574-2580)
IEEE DOI
2008
Training, Deep learning, Image resolution, Image color analysis,
Cameras, Feature extraction, Pattern recognition.
Feature extraction, Cameras, Trajectory, Task analysis, Training,
Urban areas, Servers
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Zhu, X.,
Luo, Z.,
Fu, P.,
Ji, X.,
VOC-RelD: Vehicle Re-identification based on
Vehicle-Orientation-Camera,
City20(2566-2573)
IEEE DOI
2008
Cameras, Shape, Training, Task analysis, Feature extraction,
Image color analysis, Urban areas
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Gao, C.,
Hu, Y.,
Zhang, Y.,
Yao, R.,
Zhou, Y.,
Zhao, J.,
Vehicle Re-Identification Based on Complementary Features,
City20(2520-2526)
IEEE DOI
2008
Feature extraction, Training, Task analysis, Encoding, Testing,
Information filters
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Sebastian, C.,
Imbriaco, R.,
Bondarev, E.,
de With, P.H.N.,
Dual Embedding Expansion for Vehicle Re-identification,
City20(2475-2484)
IEEE DOI
2008
Feature extraction, Task analysis, Image retrieval,
Image color analysis, Computational modeling, Frequency modulation
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He, S.,
Luo, H.,
Chen, W.,
Zhang, M.,
Zhang, Y.,
Wang, F.,
Li, H.,
Jiang, W.,
Multi-Domain Learning and Identity Mining for Vehicle
Re-Identification,
City20(2485-2493)
IEEE DOI
2008
Data models, Task analysis, Testing, Feature extraction, Urban areas,
Data mining, Computer vision
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Liu, K.,
Xu, Z.,
Hou, Z.,
Zhao, Z.,
Su, F.,
Further Non-local and Channel Attention Networks for Vehicle
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City20(2494-2500)
IEEE DOI
2008
Feature extraction, Task analysis, Training, Kernel, Visualization,
Network architecture, Convolution
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Eckstein, V.,
Schumann, A.,
Specker, A.,
Large Scale Vehicle Re-Identification by Knowledge Transfer from
Simulated Data and Temporal Attention,
City20(2626-2631)
IEEE DOI
2008
Data models, Cameras, Task analysis, Adaptation models,
Computational modeling, Machine learning, Visualization
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Zhuge, C.,
Peng, Y.,
Li, Y.,
Ai, J.,
Chen, J.,
Attribute-guided Feature Extraction and Augmentation Robust Learning
for Vehicle Re-identification,
City20(2632-2637)
IEEE DOI
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Feature extraction, Training, Image color analysis, Robustness,
Cameras, Task analysis, Automobiles
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Chu, R.H.[Rui-Hang],
Sun, Y.F.[Yi-Fan],
Li, Y.D.[Ya-Dong],
Liu, Z.[Zheng],
Zhang, C.[Chi],
Wei, Y.C.[Yi-Chen],
Vehicle Re-Identification with Viewpoint-Aware Metric Learning,
ICCV19(8281-8290)
IEEE DOI
2004
image recognition, learning (artificial intelligence),
road vehicles, traffic engineering computing, similar viewpoints,
Face recognition
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Khorramshahi, P.,
Kumar, A.,
Peri, N.,
Rambhatla, S.S.,
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Chellappa, R.,
A Dual-Path Model With Adaptive Attention for Vehicle
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ICCV19(6131-6140)
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Code, Re-Identification.
WWW Link. feature extraction, learning (artificial intelligence),
vehicle re-identification, attention models, Task analysis
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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
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image processing, traffic engineering computing, aerial imagery,
UAV-mounted cameras, UAV-based vehicle ReID dataset,
Visualization
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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
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Wu, M.J.[Ming-Jie],
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MMMod20(II:88-99).
Springer DOI
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Wang, S.Q.[Shi-Qi],
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VERI-Wild: A Large Dataset and a New Method for Vehicle
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Part-Regularized Near-Duplicate Vehicle Re-Identification,
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IEEE DOI
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Yang, X.,
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Xing, J.,
Vehicle Re-Identification by Multi-Grain Learni,
ICIP19(3113-3117)
IEEE DOI
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Vehicle re-identification, Multi-grain ranking loss
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Alfasly, S.A.S.,
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Jin, X.,
Zhao, Q.,
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Variational Representation Learning for Vehicle Re-Identificati,
ICIP19(3118-3122)
IEEE DOI
1910
Deep Learning, LSTM, Variational Features, Vehicle Re-Identification
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de Oliveira, I.O.,
Fonseca, K.V.O.,
Minetto, R.,
A Two-Stream Siamese Neural Network for Vehicle Re-Identification by
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ICIP19(669-673)
IEEE DOI
1910
Vehicle Re-identification, Siamese Neural Networks,
Vehicle Matching, Travel Time Estimation
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Wei, X.S.[Xiu-Shen],
Zhang, C.L.[Chen-Lin],
Liu, L.Q.[Ling-Qiao],
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Coarse-to-Fine: A RNN-Based Hierarchical Attention Model for Vehicle
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ACCV18(II:575-591).
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City18(166-1665)
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Videos, Urban areas, Task analysis, Artificial intelligence,
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Feature extraction, Bayes methods, Fuses, Licenses, Training,
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Convolutional neural networks, Linear programming,
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Feature extraction, Videos, Automobiles, Task analysis, Urban areas,
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Feature extraction, Image color analysis, Computer architecture,
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IPTA17(1-6)
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convolution, feature extraction, feedforward neural nets,
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Cameras, Feature extraction, Image color analysis, Measurement,
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Computational modeling, Face recognition, Feature extraction,
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computer vision, feature extraction, image retrieval,
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feature extraction, image retrieval, spatiotemporal phenomena,
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image colour analysis
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Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Vehicle Tracking, Speed Computations, Vehicle Speed, Traffic Speed .