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Vehicle Re-Identification With Dynamic Time Windows for Vehicle Passage
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1805
automobiles, convolution, feedforward neural nets,
image representation, inference mechanisms,
spatially concatenated ConvNet
BibRef
Zhou, Y.,
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Viewpoint-Aware Attentive Multi-view Inference for Vehicle
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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
BibRef
Liu, X.C.[Xin-Chen],
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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
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Elsevier DOI
1905
Survey, Vehicle Re-Identification. Re-identification, Hand-crafted methods,
Convolutional neural network, Traffic analysis
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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
BibRef
Lou, Y.H.[Yi-Hang],
Bai, Y.[Yan],
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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
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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
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Messoussi, O.[Oumayma],
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Lamarre, F.[Francois],
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Vehicle Detection and Tracking from Surveillance Cameras in Urban
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ISVC21(II:191-202).
Springer DOI
2112
BibRef
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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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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
panhel, J.[Jakub],
Sochor, J.[Jakub],
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CVIU(192), 2020, pp. 102883.
Elsevier DOI
2002
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Zapletal, D.,
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Vehicle Re-identification for Automatic Video Traffic Surveillance,
Traffic16(1568-1574)
IEEE DOI
1612
BibRef
Tumrani, S.[Saifullah],
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Lin, H.Y.[Hao-Yang],
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Partial attention and multi-attribute learning for vehicle
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PRL(138), 2020, pp. 290-297.
Elsevier DOI
1806
Vehicle re-identification, Keypoint detection, Multi-branch network
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Wang, Y.F.[Yue-Feng],
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IVC(104), 2020, pp. 104008.
Elsevier DOI
2012
Vehicle re-identification, Unsupervised,
Discriminatory local area, View discrimination, Cross-view
BibRef
Wang, H.,
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Chen, D.,
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Zhao, T.,
Fu, X.,
Attribute-Guided Feature Learning Network for Vehicle
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MultMedMag(27), No. 4, October 2020, pp. 112-121.
IEEE DOI
2012
Task analysis, Image color analysis, Training, Feature extraction,
Smoothing methods, Visualization, Frequency modulation,
Attribute-based Label Smoothing Loss
BibRef
Chen, X.,
Sui, H.,
Fang, J.,
Feng, W.,
Zhou, M.,
Vehicle Re-Identification Using Distance-Based Global and Partial
Multi-Regional Feature Learning,
ITS(22), No. 2, February 2021, pp. 1276-1286.
IEEE DOI
2102
Spatiotemporal phenomena, Visualization, Cameras,
Feature extraction, Interference, vehicle re-identification
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Teng, S.,
Zhang, S.,
Huang, Q.,
Sebe, N.,
Multi-View Spatial Attention Embedding for Vehicle Re-Identification,
CirSysVideo(31), No. 2, February 2021, pp. 816-827.
IEEE DOI
2102
Feature extraction, Task analysis, Measurement, Visualization,
Computer science, Training, Neural networks,
multi-view
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Jin, Y.[Yi],
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Li, Y.D.[Yi-Dong],
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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,
multi-view vehicle re-identification
BibRef
Hsu, H.M.[Hung-Min],
Cai, J.R.[Jia-Rui],
Wang, Y.Z.[Yi-Zhou],
Hwang, J.N.[Jenq-Neng],
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Multi-Target Multi-Camera Tracking of Vehicles Using Metadata-Aided
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IP(30), 2021, pp. 5198-5210.
IEEE DOI
2106
Cameras, Trajectory, Target tracking, Task analysis, Metadata,
Feature extraction, Image color analysis, MTMCT,
hierarchical clustering
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Roman-Jimenez, G.[Geoffrey],
Guyot, P.[Patrice],
Malon, T.[Thierry],
Chambon, S.[Sylvie],
Charvillat, V.[Vincent],
Crouzil, A.[Alain],
Péninou, A.[André],
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Improving vehicle re-identification using CNN latent spaces: Metrics
comparison and track-to-track extension,
IET-CV(15), No. 2, 2021, pp. 85-98.
DOI Link
2106
BibRef
Boukerche, A.[Azzedine],
Ma, X.R.[Xi-Ren],
Vision-Based Autonomous Vehicle Recognition:
A New Challenge for Deep Learning-Based Systems,
Surveys(54), No. 4, May 2021, pp. xx-yy.
DOI Link
2107
Deep learning, vehicle make and model recognition,
vehicle re-identification, video surveillance, fine-grained recognition
BibRef
Zheng, Z.D.[Zhe-Dong],
Ruan, T.[Tao],
Wei, Y.C.[Yun-Chao],
Yang, Y.[Yi],
Mei, T.[Tao],
VehicleNet: Learning Robust Visual Representation for Vehicle
Re-Identification,
MultMed(23), 2021, pp. 2683-2693.
IEEE DOI
2109
Training, Robustness, Adaptation models, Data models, Automobiles,
Cameras, Feature extraction, Vehicle re-identification,
convolutional neural networks
BibRef
Zheng, Z.D.[Zhe-Dong],
Jiang, M.Y.[Min-Yue],
Wang, Z.G.[Zhi-Gang],
Wang, J.[Jian],
Bai, Z.C.[Ze-Chen],
Zhang, X.M.[Xuan-Meng],
Yu, X.[Xin],
Tan, X.[Xiao],
Yang, Y.[Yi],
Wen, S.L.[Shi-Lei],
Ding, E.[Errui],
Going Beyond Real Data: A Robust Visual Representation for Vehicle
Re-identification,
City20(2550-2558)
IEEE DOI
2008
Training, Visualization, Robustness, Feature extraction,
Task analysis, Image color analysis, Fuses
BibRef
Peng, J.J.[Jin-Jia],
Jiang, G.Q.[Guang-Qi],
Wang, H.B.[Hui-Bing],
Generalized multiple sparse information fusion for vehicle
re-identification,
JVCIR(79), 2021, pp. 103207.
Elsevier DOI
2109
Vehicle re-identification, Hierarchical attention network, Multi-views
BibRef
Zhu, W.Q.[Wen-Qian],
Wang, Z.Y.[Zhong-Yuan],
Hu, R.M.[Rui-Min],
Li, D.S.[Deng-Shi],
From Semantic to Spatial Awareness: Vehicle Reidentification With
Multiple Attention Mechanisms,
MultMedMag(28), No. 3, July 2021, pp. 32-41.
IEEE DOI
2109
Feature extraction, Semantics, Automotive components,
Visualization, Video surveillance, Licenses, Vehicular ad hoc networks
BibRef
Xiong, Z.X.[Zhong-Xia],
Li, M.[Ming],
Ma, Y.[Yalong],
Wu, X.[Xinkai],
Vehicle Re-Identification With Image Processing and Car-Following
Model Using Multiple Surveillance Cameras From Urban Arterials,
ITS(22), No. 12, December 2021, pp. 7619-7630.
IEEE DOI
2112
Cameras, Data mining, Surveillance, Detectors, Trajectory,
Feature extraction, Surveillance video, image processing,
IDM car-following model
BibRef
Lin, X.M.[Xian-Ming],
Li, R.[Run],
Zheng, X.[Xiawu],
Peng, P.[Pai],
Wu, Y.J.[Yong-Jian],
Huang, F.Y.[Fei-Yue],
Ji, R.R.[Rong-Rong],
Aggregating Global and Local Visual Representation for Vehicle
Re-IDentification,
MultMed(23), 2021, pp. 3968-3977.
IEEE DOI
2112
Measurement, Visualization, Inspection, Image color analysis,
Lighting, Vehicles, Vehicle Re-ID,
MCMS-Siam network
BibRef
Li, Y.D.[Yi-Dong],
Liu, K.[Kai],
Jin, Y.[Yi],
Wang, T.[Tao],
Lin, W.P.[Wei-Peng],
VARID: Viewpoint-Aware Re-IDentification of Vehicle Based on Triplet
Loss,
ITS(23), No. 2, February 2022, pp. 1381-1390.
IEEE DOI
2202
Task analysis, Feature extraction, Measurement, Visualization,
Benchmark testing, Robustness, Training, Vehicle re-identification,
triplet loss
BibRef
Chen, Y.B.[Yan-Bing],
Ke, W.[Wei],
Lin, H.[Hong],
Lam, C.T.[Chan-Tong],
Lv, K.[Kai],
Sheng, H.[Hao],
Xiong, Z.[Zhang],
Local perspective based synthesis for vehicle re-identification: A
transformation state adversarial method,
JVCIR(83), 2022, pp. 103432.
Elsevier DOI
2202
Vehicle re-identification, Data synthesis,
Local-region perspective transformation, Parameter generator network
BibRef
Wang, Q.[Qi],
Min, W.D.[Wei-Dong],
Han, Q.[Qing],
Liu, Q.[Qian],
Zha, C.[Cheng],
Zhao, H.Y.[Hao-Yu],
Wei, Z.[Zitai],
Inter-Domain Adaptation Label for Data Augmentation in Vehicle
Re-Identification,
MultMed(24), 2022, pp. 1031-1041.
IEEE DOI
2203
Training, Semisupervised learning, Cameras, Training data,
Data models, Adaptation models, Smoothing methods,
inter-domain adaptation label smoothing regularization
BibRef
Huang, Y.[Yue],
Liang, B.[Borong],
Xie, W.P.[Wei-Ping],
Liao, Y.H.[Ying-Hao],
Kuang, Z.Y.[Zhen-Yu],
Zhuang, Y.H.[Yi-Hong],
Ding, X.H.[Xing-Hao],
Dual Domain Multi-Task Model for Vehicle Re-Identification,
ITS(23), No. 4, April 2022, pp. 2991-2999.
IEEE DOI
2204
Image color analysis, Task analysis, Feature extraction,
Automobiles, Training, Licenses, Frequency-domain analysis,
vehicle re-identification
BibRef
Shen, F.[Fei],
Zhu, J.Q.[Jian-Qing],
Zhu, X.B.[Xia-Bin],
Xie, Y.[Yi],
Huang, J.C.[Jing-Chang],
Exploring Spatial Significance via Hybrid Pyramidal Graph Network for
Vehicle Re-Identification,
ITS(23), No. 7, July 2022, pp. 8793-8804.
IEEE DOI
2207
Feature extraction, Detectors, Annotations,
Visualization, Task analysis, Lighting, Deep learning, graph network,
vehicle re-identification
BibRef
Tu, J.Z.[Jing-Zheng],
Chen, C.[Cailian],
Huang, X.L.[Xiao-Lin],
He, J.P.[Jian-Ping],
Guan, X.P.[Xin-Ping],
DFR-ST: Discriminative feature representation with spatio-temporal
cues for vehicle re-identification,
PR(131), 2022, pp. 108887.
Elsevier DOI
2208
Vehicle re-identification, Computer vision, Deep learning,
Attention mechanism, Video surveillance
BibRef
Zheng, A.[Aihua],
Sun, X.[Xia],
Li, C.L.[Cheng-Long],
Tang, J.[Jin],
Viewpoint-Aware Progressive Clustering for Unsupervised Vehicle
Re-Identification,
ITS(23), No. 8, August 2022, pp. 11422-11435.
IEEE DOI
2208
Task analysis, Clustering algorithms, Unsupervised learning,
Cameras, Annotations, Space vehicles, Shape, Viewpoint-aware,
unsupervised learning
BibRef
Zhang, C.[Cheng],
Chen, B.Y.[Bi Yu],
Lam, W.H.K.[William H. K.],
Ho, H.W.,
Shi, X.M.[Xiao-Meng],
Yang, X.G.[Xiao-Guang],
Ma, W.[Wei],
Wong, S.C.,
Chow, A.H.F.[Andy H. F.],
Vehicle Re-identification for Lane-level Travel Time Estimations on
Congested Urban Road Networks Using Video Images,
ITS(23), No. 8, August 2022, pp. 12877-12893.
IEEE DOI
2208
Roads, Feature extraction, Estimation, Standards, Detectors, Cameras,
Visualization, Vehicle re-identification,
video images
BibRef
Bai, Y.[Yan],
Liu, J.[Jun],
Lou, Y.H.[Yi-Hang],
Wang, C.[Ce],
Duan, L.Y.[Ling-Yu],
Disentangled Feature Learning Network and a Comprehensive Benchmark
for Vehicle Re-Identification,
PAMI(44), No. 10, October 2022, pp. 6854-6871.
IEEE DOI
2209
Cameras, Training, Meteorology, Benchmark testing, Surveillance,
Lighting, Feature extraction, Vehicle re-identification,
disentangled learning
BibRef
Li, H.C.[Hong-Chao],
Li, C.L.[Cheng-Long],
Zheng, A.[Aihua],
Tang, J.[Jin],
Luo, B.[Bin],
Attribute and State Guided Structural Embedding Network for Vehicle
Re-Identification,
IP(31), 2022, pp. 5949-5962.
IEEE DOI
2209
Cameras, Image color analysis, Feature extraction, Task analysis,
Space vehicles, Measurement, Force, Vehicle re-identification,
global structural embedding
BibRef
Sun, W.[Wei],
Dai, G.Z.[Guang-Zhao],
Zhang, X.R.[Xiao-Rui],
He, X.Z.[Xiao-Zheng],
Chen, X.[Xuan],
TBE-Net: A Three-Branch Embedding Network With Part-Aware Ability and
Feature Complementary Learning for Vehicle Re-Identification,
ITS(23), No. 9, September 2022, pp. 14557-14569.
IEEE DOI
2209
Feature extraction, Cameras, Image color analysis,
Information science, Sun, Training, Technological innovation, embedding
BibRef
Lu, M.M.[Ming-Ming],
Xu, Y.C.[Yong-Chuan],
Li, H.F.[Hai-Feng],
Vehicle Re-Identification Based on UAV Viewpoint: Dataset and Method,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link
2209
BibRef
Tu, M.F.[Ming-Fei],
Zhu, K.[Kuan],
Guo, H.Y.[Hai-Yun],
Miao, Q.H.[Qing-Hai],
Zhao, C.Y.[Chao-Yang],
Zhu, G.[Guibo],
Qiao, H.[Honglin],
Huang, G.[Gaopan],
Tang, M.[Ming],
Wang, J.Q.[Jin-Qiao],
Multi-Granularity Mutual Learning Network for Object
Re-Identification,
ITS(23), No. 9, September 2022, pp. 15178-15189.
IEEE DOI
2209
Feature extraction, Visualization, Task analysis,
Intelligent transportation systems, Image reconstruction, solving jigsaw puzzle
BibRef
Tran, D.N.N.[Duong Nguyen-Ngoc],
Pham, L.H.[Long Hoang],
Jeon, H.J.[Hyung-Joon],
Nguyen, H.H.[Huy-Hung],
Jeon, H.M.[Hyung-Min],
Tran, T.H.P.[Tai Huu-Phuong],
Jeon, J.W.[Jae Wook],
A Robust Traffic-Aware City-Scale Multi-Camera Vehicle Tracking Of
Vehicles,
AICity22(3149-3158)
IEEE DOI
2210
Target tracking, Vehicle detection, Surveillance, Urban areas,
Traffic control, Feature extraction, Trajectory
BibRef
Li, Z.Y.[Zhi-Yong],
Luo, Y.Z.[Yun-Zhong],
Li, Q.[Qiaochu],
Song, L.[Lulu],
Liu, W.Y.[Wei-Yi],
Mixed-attention-based regional soft partition network for vehicle
reidentification,
IET-IPR(16), No. 13, 2022, pp. 3648-3658.
DOI Link
2210
BibRef
Yang, H.[Hao],
Cai, J.R.[Jia-Rui],
Zhu, M.[Meixin],
Liu, C.X.[Chen-Xi],
Wang, Y.[Yinhai],
Traffic-Informed Multi-Camera Sensing (TIMS) System Based on Vehicle
Re-Identification,
ITS(23), No. 10, October 2022, pp. 17189-17200.
IEEE DOI
2210
Sensors, Feature extraction, Roads, Information retrieval,
Data mining, Videos, Traffic sensing,
vehicle re-identification
BibRef
Liu, C.S.[Chun-Sheng],
Song, Y.[Ye],
Chang, F.L.[Fa-Liang],
Li, S.[Shuang],
Ke, R.M.[Rui-Min],
Wang, Y.H.[Yin-Hai],
Posture Calibration Based Cross-View and Hard-Sensitive Metric
Learning for UAV-Based Vehicle Re-Identification,
ITS(23), No. 10, October 2022, pp. 19246-19257.
IEEE DOI
2210
Measurement, Feature extraction, Calibration, Training,
Autonomous aerial vehicles, Surveillance,
cross-view re-identification
BibRef
Li, H.C.[Hong-Chao],
Li, C.L.[Cheng-Long],
Zheng, A.[Aihua],
Tang, J.[Jin],
Luo, B.[Bin],
MsKAT: Multi-Scale Knowledge-Aware Transformer for Vehicle
Re-Identification,
ITS(23), No. 10, October 2022, pp. 19557-19568.
IEEE DOI
2210
Transformers, Visualization, Feature extraction,
Image color analysis, Semantics, Knowledge based systems, multi-scale
BibRef
Lu, Z.F.[Ze-Feng],
Lin, R.H.[Rong-Hao],
Lou, X.[Xulei],
Zheng, L.F.[Li-Feng],
Hu, H.F.[Hai-Feng],
Identity-Unrelated Information Decoupling Model for Vehicle
Re-Identification,
ITS(23), No. 10, October 2022, pp. 19001-19015.
IEEE DOI
2210
Feature extraction, Transformers, Task analysis,
Generative adversarial networks, Image color analysis,
information decoupling
BibRef
Qian, W.[Wen],
He, Z.[Zhiqun],
Chen, C.[Chen],
Peng, S.[Silong],
Navigating Diverse Salient Features for Vehicle Re-Identification,
ITS(23), No. 12, December 2022, pp. 24578-24587.
IEEE DOI
2212
Navigation, Task analysis, Image color analysis, Boosting,
Feature extraction, Benchmark testing, Space vehicles,
cross-space constraints
BibRef
Tang, L.[Lisha],
Wang, Y.[Yi],
Chau, L.P.[Lap-Pui],
Weakly-Supervised Part-Attention and Mentored Networks for Vehicle
Re-Identification,
CirSysVideo(32), No. 12, December 2022, pp. 8887-8898.
IEEE DOI
2212
Feature extraction, Representation learning, Location awareness,
Annotations, Lighting, Clutter, Vehicle re-identification,
multi-task learning
BibRef
Zhu, W.Q.[Wen-Qian],
Wang, Z.Y.[Zhong-Yuan],
Wang, X.C.[Xiao-Chen],
Hu, R.[Ruimin],
Liu, H.[Huikai],
Liu, C.[Cheng],
Wang, C.[Chao],
Li, D.[Dengshi],
A Dual Self-Attention mechanism for vehicle re-Identification,
PR(137), 2023, pp. 109258.
Elsevier DOI
2302
Cross-region attention, Dual self-attention,
Multi-attention network, Vehicle re-identification, Feature embedding
BibRef
Sun, Z.[Ziruo],
Nie, X.[Xiushan],
Bi, X.P.[Xiao-Peng],
Wang, S.H.[Shao-Hua],
Yin, Y.L.[Yi-Long],
Detail enhancement-based vehicle re-identification with
orientation-guided re-ranking,
PR(137), 2023, pp. 109304.
Elsevier DOI
2302
Vehicle re-identification, Detail enhancement, Re-ranking
BibRef
Lu, Z.F.[Ze-Feng],
Lin, R.[Ronghao],
Hu, H.F.[Hai-Feng],
MART: Mask-Aware Reasoning Transformer for Vehicle Re-Identification,
ITS(24), No. 2, February 2023, pp. 1994-2009.
IEEE DOI
2302
Feature extraction, Transformers, Data mining, Semantics, Cognition,
Training, Task analysis, Vehicle re-identification, transformers,
cross-image learning
BibRef
Wei, R.[Ran],
Gu, J.Y.[Jian-Yang],
He, S.[Shuting],
Jiang, W.[Wei],
Transformer-Based Domain-Specific Representation for Unsupervised
Domain Adaptive Vehicle Re-Identification,
ITS(24), No. 3, March 2023, pp. 2935-2946.
IEEE DOI
2303
Transformers, Task analysis, Adaptation models, Encoding, Training,
Representation learning, Benchmark testing, clustering
BibRef
Li, M.[Ming],
Liu, J.[Jun],
Zheng, C.[Ce],
Huang, X.M.[Xin-Ming],
Zhang, Z.[Ziming],
Exploiting Multi-View Part-Wise Correlation via an Efficient
Transformer for Vehicle Re-Identification,
MultMed(25), 2023, pp. 919-929.
IEEE DOI
2303
Transformers, Correlation, Feature extraction, Visualization,
Training, Benchmark testing, Task analysis, Correlation exploiting,
vehicle re-identification
BibRef
Li, W.[Wei],
Guo, H.Y.[Hai-Yun],
Dong, H.H.[Hong-Hui],
Tang, M.[Ming],
Zhou, Y.[Yue],
Wang, J.Q.[Jin-Qiao],
Bi-Level Implicit Semantic Data Augmentation for Vehicle
Re-Identification,
ITS(24), No. 4, April 2023, pp. 4364-4376.
IEEE DOI
2304
Semantics, Training, Space vehicles, Data models, Feature extraction,
Training data, Robustness, Vehicle re-identification,
triplet-based ranking constraint
BibRef
Wang, Q.[Qi],
Zhong, Y.L.[Yu-Ling],
Min, W.D.[Wei-Dong],
Zhao, H.Y.[Hao-Yu],
Gai, D.[Di],
Han, Q.[Qing],
Dual similarity pre-training and domain difference encouragement
learning for vehicle re-identification in the wild,
PR(139), 2023, pp. 109513.
Elsevier DOI
2304
Vehicle re-identification, Unsupervised domain adaptation,
Dual constraint label smoothing regularization loss,
Pseudo label refinement
BibRef
Lu, Z.F.[Ze-Feng],
Lin, R.[Ronghao],
He, Q.[Qiaolin],
Hu, H.F.[Hai-Feng],
Mask-Aware Pseudo Label Denoising for Unsupervised Vehicle
Re-Identification,
ITS(24), No. 4, April 2023, pp. 4333-4347.
IEEE DOI
2304
Feature extraction, Cameras, Space vehicles, Task analysis,
Supervised learning, Noise reduction, Adaptation models,
pseudo labels refining
BibRef
Zhang, Q.[Qian],
Zhang, M.X.[Ming-Xin],
Liu, J.[Jinghe],
He, X.Y.[Xuan-Yu],
Song, R.[Ran],
Zhang, W.[Wei],
Unsupervised Maritime Vessel Re-Identification With Multi-Level
Contrastive Learning,
ITS(24), No. 5, May 2023, pp. 5406-5418.
IEEE DOI
2305
Training, Task analysis, Cameras, Unsupervised learning,
Surveillance, Representation learning, unsupervised learning
BibRef
Kamenou, E.[Eleni],
del Rincon, J.M.[Jesus Martinez],
Miller, P.[Paul],
Devlin-Hill, P.[Patricia],
Closing the Domain Gap for Cross-modal Visible-Infrared Vehicle
Re-identification,
ICPR22(2728-2734)
IEEE DOI
2212
Measurement, Visualization, Data visualization, Benchmark testing,
Feature extraction, Sensors
BibRef
Chen, H.[Haobo],
Liu, Y.[Yang],
Huang, Y.[Yang],
Ke, W.[Wei],
Sheng, H.[Hao],
Partition and Reunion: A Viewpoint-Aware Loss for Vehicle
Re-Identification,
ICIP22(2246-2250)
IEEE DOI
2211
Benchmark testing, Task analysis, Vehicle re-identification,
viewpoint-aware, loss function, representation learning
BibRef
Li, M.[Manyu],
Wei, M.[Mengwan],
He, X.[Xin],
Shen, F.[Fei],
Enhancing Part Features via Contrastive Attention Module for Vehicle
Re-identification,
ICIP22(1816-1820)
IEEE DOI
2211
Part feature, contrastive attention, vehicle re-identification
BibRef
Sommer, L.[Lars],
Krüger, W.[Wolfgang],
Usage of Vehicle Re-Identification Models for Improved Persistent
Multiple Object Tracking in Wide Area Motion Imagery,
ICIP22(331-335)
IEEE DOI
2211
Representation learning, Visualization, Surveillance,
Object detection, Feature extraction, Multitasking, Data models,
vehicle re-identification
BibRef
Qian, W.[Wen],
Luo, H.[Hao],
Peng, S.[Silong],
Wang, F.[Fan],
Chen, C.[Chen],
Li, H.[Hao],
Unstructured Feature Decoupling for Vehicle Re-identification,
ECCV22(XIV:336-353).
Springer DOI
2211
BibRef
Li, F.[Fei],
Wang, Z.[Zhen],
Nie, D.[Ding],
Zhang, S.Y.[Shi-Yi],
Jiang, X.Q.[Xing-Qun],
Zhao, X.X.[Xing-Xing],
Hu, P.[Peng],
Multi-Camera Vehicle Tracking System for AI City Challenge 2022,
AICity22(3264-3272)
IEEE DOI
2210
Vehicle detection, Urban areas, Merging,
Predictive models, Feature extraction
BibRef
Yao, H.[Hui],
Duan, Z.[Zhizhao],
Xie, Z.[Zhen],
Chen, J.[Jingbo],
Wu, X.[Xi],
Xu, D.[Duo],
Gao, Y.[Yutao],
City-Scale Multi-Camera Vehicle Tracking based on
Space-Time-Appearance Features,
AICity22(3309-3317)
IEEE DOI
2210
Interpolation, Target tracking, Object detection,
Feature extraction, Cameras, Trajectory
BibRef
Mehta, R.[Rajat],
Kaechele, M.[Markus],
Stricker, D.[Didier],
Bajcinca, N.[Naim],
Cluster-based Convolutional Baseline for Multi-Camera Vehicle
Re-identification,
CIAP22(II:541-552).
Springer DOI
2205
BibRef
He, S.T.[Shu-Ting],
Luo, H.[Hao],
Wang, P.[Pichao],
Wang, F.[Fan],
Li, H.[Hao],
Jiang, W.[Wei],
TransReID: Transformer-based Object Re-Identification,
ICCV21(14993-15002)
IEEE DOI
2203
Representation learning, Codes, Convolution, Neural networks,
Benchmark testing, Transformers, Biometrics, Image and video retrieval
BibRef
Zhao, J.J.[Jia-Jian],
Zhao, Y.F.[Yi-Fan],
Li, J.[Jia],
Yan, K.[Ke],
Tian, Y.H.[Yong-Hong],
Heterogeneous Relational Complement for Vehicle Re-identification,
ICCV21(205-214)
IEEE DOI
2203
Semantics, Benchmark testing, Position measurement, Cameras,
Recognition and classification, Image and video retrieval
BibRef
He, B.[Bing],
Li, J.[Jia],
Zhao, Y.F.[Yi-Fan],
Tian, Y.H.[Yong-Hong],
Part-Regularized Near-Duplicate Vehicle Re-Identification,
CVPR19(3992-4000).
IEEE DOI
2002
BibRef
Li, M.[Ming],
Huang, X.M.[Xin-Ming],
Zhang, Z.M.[Zi-Ming],
Self-supervised Geometric Features Discovery via Interpretable
Attention for Vehicle Re-Identification and Beyond,
ICCV21(194-204)
IEEE DOI
2203
Representation learning, Visualization, Annotations, Scalability,
Benchmark testing, Task analysis, Recognition and classification,
Image and video retrieval
BibRef
Dou, X.Z.[Xin-Ze],
Liu, Y.[Yang],
Lv, K.[Kai],
Xiong, Z.[Zhang],
Sheng, H.[Hao],
High Confidence Attribute Recognition for Vehicle Re-Identification,
ICIP21(2353-2357)
IEEE DOI
2201
Image recognition, Feature extraction, Cameras, Videos,
Vehicle re-identification, high confidence attributes,
orientation learning
BibRef
Besbes, M.D.E.[Mohamed Dhia Elhak],
Tabia, H.[Hedi],
Kessentini, Y.[Yousri],
Hamed, B.B.[Bassem Ben],
Progressive Learning With Anchoring Regularization for Vehicle
Re-Identification,
ICIP21(1154-1158)
IEEE DOI
2201
Training, Databases, Surveillance, Supervised learning,
Training data, Feature extraction, Vehicle re-identification,
anchoring regularization
BibRef
Zhao, J.N.[Jia-Nan],
Qi, F.L.[Feng-Liang],
Ren, G.Y.[Guang-Yu],
Xu, L.[Lin],
PhD Learning: Learning with Pompeiu-hausdorff Distances for
Video-based Vehicle Re-Identification,
CVPR21(2225-2235)
IEEE DOI
2111
Learning systems, Visualization, Surveillance, Resists,
Benchmark testing, Data models, Pattern recognition
BibRef
Liu, C.[Chong],
Zhang, Y.[Yuqi],
Luo, H.[Hao],
Tang, J.[Jiasheng],
Chen, W.H.[Wei-Hua],
Xu, X.Z.[Xian-Zhe],
Wang, F.[Fan],
Li, H.[Hao],
Shen, Y.D.[Yi-Dong],
City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones,
AICity21(4124-4132)
IEEE DOI
2109
Matched filters, Target tracking,
Urban areas, Feature extraction, Cameras
BibRef
Li, Y.L.[Yun-Lun],
Chin, Z.Y.[Zhi-Yi],
Chang, M.C.[Ming-Ching],
Chiang, C.K.[Chen-Kuo],
Multi-Camera Tracking By Candidate Intersection Ratio Tracklet
Matching,
AICity21(4098-4106)
IEEE DOI
2109
Measurement, Filtering, Smart cities, Visual analytics,
Vehicle detection, Pipelines, Streaming media
BibRef
Wu, M.H.[Ming-Hu],
Qian, Y.Q.[Ye-Qiang],
Wang, C.X.[Chun-Xiang],
Yang, M.[Ming],
A Multi-Camera Vehicle Tracking System based on City-Scale Vehicle
Re-ID and Spatial-Temporal Information,
AICity21(4072-4081)
IEEE DOI
2109
Visualization, Uncertainty, Urban areas, Lighting,
Feature extraction, Robustness, Data models
BibRef
Yang, K.S.[Kai-Siang],
Chen, Y.K.[Yu-Kai],
Chen, T.S.[Tsai-Shien],
Liu, C.T.[Chih-Ting],
Chien, S.Y.[Shao-Yi],
Tracklet-refined Multi-Camera Tracking based on Balanced Cross-Domain
Re-Identification for Vehicles,
AICity21(3978-3987)
IEEE DOI
2109
Training, Target tracking, Training data,
Filtering algorithms, Information filters, Data models
BibRef
Jiang, M.Y.[Min-Yue],
Zhang, X.M.[Xuan-Meng],
Yu, Y.[Yue],
Bai, Z.C.[Ze-Chen],
Zheng, Z.D.[Zhe-Dong],
Wang, Z.G.[Zhi-Gang],
Wang, J.[Jian],
Tan, X.[Xiao],
Sun, H.[Hao],
Ding, E.[Errui],
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
BibRef
Luo, H.[Hao],
Chen, W.H.[Wei-Hua],
Xu, X.Z.[Xian-Zhe],
Gu, J.Y.[Jian-Yang],
Zhang, Y.[Yuqi],
Liu, C.[Chong],
Jiang, Y.Q.[Yi-Qi],
He, S.[Shuting],
Wang, F.[Fan],
Li, H.[Hao],
An Empirical Study of Vehicle Re-Identification on the AI City
Challenge,
AICity21(4090-4097)
IEEE DOI
2109
Training, Computational modeling,
Urban areas, Training data, Data models
BibRef
Huynh, S.V.[Su V.],
Nguyen, N.H.[Nam H.],
Nguyen, N.T.[Ngoc T.],
Nguyen, V.T.[Vinh Tq.],
Huynh, C.[Chau],
Nguyen, C.[Chuong],
A Strong Baseline for Vehicle Re-Identification,
AICity21(4142-4149)
IEEE DOI
2109
Training, Target tracking, Head, Urban areas, Stacking
BibRef
Sun, Y.L.[Yong-Li],
Li, W.[Wenpeng],
Wei, H.[Hua],
Zhang, L.T.[Long-Tao],
Tian, J.H.[Jia-Hao],
Sun, G.Z.[Guang-Ze],
Wang, G.[Gang],
Cao, J.L.[Jun-Liang],
Zhao, Z.F.[Zhi-Feng],
Ding, J.F.[Jun-Feng],
Progressive Data Mining and Adaptive Weighted Multi-Model Ensemble
for Vehicle Re-Identification,
AICity21(4196-4201)
IEEE DOI
2109
Training, Adaptation models, Computational modeling,
Image matching, Urban areas, Lighting, Data models
BibRef
Kamenou, E.[Eleni],
del Rincon, J.M.[Jesus Martinez],
Miller, P.[Paul],
Devlin-Hill, P.[Patricia],
Multi-level Deep Learning Vehicle Re-identification using
Ranked-based Loss Functions,
ICPR21(9099-9106)
IEEE DOI
2105
Measurement, Space vehicles, Deep learning, Annotations,
System performance, Cameras, Pattern recognition
BibRef
Xu, Z.M.[Zhe-Ming],
Wei, L.[Lili],
Lang, C.[Congyan],
Feng, S.H.[Song-He],
Wang, T.[Tao],
Bors, A.G.[Adrian G.],
HSS-GCN: A Hierarchical Spatial Structural Graph Convolutional Network
for Vehicle Re-identification,
IUC20(356-364).
Springer DOI
2103
BibRef
Xie, Y.,
Zhu, J.,
Zeng, H.,
Cai, C.,
Zheng, L.,
Learning Matching Behavior Differences for Compressing Vehicle
Re-identification Models,
VCIP20(523-526)
IEEE DOI
2102
Training, Testing, Probes, Image coding, Loss measurement,
Computational modeling, Trajectory, Deep Learning,
Vehicle Re-identification
BibRef
Khorramshahi, P.[Pirazh],
Peri, N.[Neehar],
Chen, J.C.[Jun-Cheng],
Chellappa, R.[Rama],
The Devil Is in the Details:
Self-supervised Attention for Vehicle Re-identification,
ECCV20(XIV:369-386).
Springer DOI
2011
BibRef
Chen, T.S.[Tsai-Shien],
Liu, C.T.[Chih-Ting],
Wu, C.W.[Chih-Wei],
Chien, S.Y.[Shao-Yi],
Orientation-aware Vehicle Re-identification with Semantics-guided Part
Attention Network,
ECCV20(II:330-346).
Springer DOI
2011
BibRef
Lee, S.,
Park, E.,
Yi, H.,
Lee, S.H.,
StRDAN: Synthetic-to-Real Domain Adaptation Network for Vehicle
Re-Identification,
City20(2590-2597)
IEEE DOI
2008
Adaptation models, Feature extraction, Task analysis, Training,
Data models, Image color analysis, Urban areas
BibRef
Meng, D.,
Li, L.,
Liu, X.,
Li, Y.,
Yang, S.,
Zha, Z.,
Gao, X.,
Wang, S.,
Huang, Q.,
Parsing-Based View-Aware Embedding Network for Vehicle
Re-Identification,
CVPR20(7101-7110)
IEEE DOI
2008
Feature extraction, Task analysis, Cameras,
Training, Image color analysis, Fuses
BibRef
Chen, T.,
Lee, M.,
Liu, C.,
Chien, S.,
Viewpoint-aware Channel-wise Attentive Network for Vehicle
Re-identification,
City20(2448-2455)
IEEE DOI
2008
Feature extraction, Estimation, Cameras, Task analysis, Semantics,
Detectors, Data mining
BibRef
Fernández, M.[Marta],
Moral, P.[Paula],
García-Martín, Á.[Álvaro],
Martínez, J.M.[José M.],
Vehicle Re-Identification based on Ensembling Deep Learning Features
including a Synthetic Training Dataset, Orientation and Background
Features, and Camera Verification.,
AICity21(4063-4071)
IEEE DOI
2109
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
Liu, K.,
Xu, Z.,
Hou, Z.,
Zhao, Z.,
Su, F.,
Further Non-local and Channel Attention Networks for Vehicle
Re-identification,
City20(2494-2500)
IEEE DOI
2008
Feature extraction, Task analysis, Training, Kernel, Visualization,
Network architecture, Convolution
BibRef
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
BibRef
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
2008
Feature extraction, Training, Image color analysis, Robustness,
Cameras, Task analysis, Automobiles
BibRef
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
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],
Bai, Y.[Yan],
Liu, J.[Jun],
Wang, S.Q.[Shi-Qi],
Duan, L.Y.[Ling-Yu],
VERI-Wild: A Large Dataset and a New Method for Vehicle
Re-Identification in the Wild,
CVPR19(3230-3238).
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
Re-identification,
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
Porrello, A.[Angelo],
Bergamini, L.[Luca],
Calderara, S.[Simone],
Robust Re-identification by Multiple Views Knowledge Distillation,
ECCV20(X:93-110).
Springer DOI
2011
Code, Re-Identification.
WWW Link.
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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,
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
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 .