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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
for Urban Surveillance,
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
BibRef
Messoussi, O.[Oumayma],
de Magalhăes, F.G.[Felipe Gohring],
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
Ooi, H.L.[Hui-Lee],
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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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Vehicle re-identification based on unsupervised local area detection
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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.,
Jiang, G.,
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],
Li, C.N.[Chen-Ning],
Li, Y.D.[Yi-Dong],
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Model Latent Views with Multi-Center Metric Learning for Vehicle
Re-Identification,
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, 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.Q.[Zhi-Qun],
Chen, C.[Chen],
Peng, S.L.[Si-Long],
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.M.[Rui-Min],
Liu, H.K.[Hui-Kai],
Liu, C.[Cheng],
Wang, C.[Chao],
Li, D.S.[Deng-Shi],
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.H.[Rong-Hao],
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.T.[Shu-Ting],
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.M.[Zi-Ming],
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.H.[Rong-Hao],
He, Q.L.[Qiao-Lin],
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.H.[Jing-He],
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
Meng, D.[Dechao],
Li, L.[Liang],
Liu, X.J.[Xue-Jing],
Gao, L.[Lin],
Huang, Q.M.[Qing-Ming],
Viewpoint Alignment and Discriminative Parts Enhancement in 3D Space
for Vehicle ReID,
MultMed(25), 2023, pp. 2954-2965.
IEEE DOI
2309
BibRef
Chen, Y.B.[Yong-Biao],
Zhang, S.[Sheng],
Liu, F.X.[Fang-Xin],
Wu, C.G.[Cheng-Gang],
Guo, K.C.[Kai-Cheng],
Qi, Z.W.[Zheng-Wei],
DVHN: A Deep Hashing Framework for Large-Scale Vehicle
Re-Identification,
ITS(24), No. 9, September 2023, pp. 9268-9280.
IEEE DOI
2310
BibRef
Zheng, A.[Aihua],
Zhang, C.B.[Chao-Bin],
Li, C.L.[Cheng-Long],
Tang, J.[Jin],
Tan, C.[Chang],
Multi-Query Vehicle Re-Identification: Viewpoint-Conditioned Network,
Unified Dataset and New Metric,
IP(32), 2023, pp. 5948-5960.
IEEE DOI Code:
WWW Link.
2311
BibRef
He, Q.L.[Qiao-Lin],
Lu, Z.F.[Ze-Feng],
Wang, Z.H.[Zi-Han],
Hu, H.F.[Hai-Feng],
Graph-Based Progressive Fusion Network for Multi-Modality Vehicle
Re-Identification,
ITS(24), No. 11, November 2023, pp. 12431-12447.
IEEE DOI
2311
BibRef
Pang, X.[Xiyu],
Tian, X.[Xin],
Nie, X.[Xiushan],
Yin, Y.L.[Yi-Long],
Jiang, G.[Gangwu],
Vehicle re-identification based on grouping aggregation attention and
cross-part interaction,
JVCIR(97), 2023, pp. 103937.
Elsevier DOI
2312
Vehicle re-identification, Grouping aggregation attention,
Cross-part interaction
BibRef
Kuang, Z.Y.[Zhen-Yu],
He, C.C.[Chu-Chu],
Huang, Y.[Yue],
Ding, X.H.[Xing-Hao],
Li, H.F.[Hua-Feng],
Joint Image and Feature Levels Disentanglement for Generalizable
Vehicle Re-identification,
ITS(24), No. 12, December 2023, pp. 15259-15273.
IEEE DOI
2312
BibRef
Lian, J.W.[Jia-Wei],
Wang, D.H.[Da-Han],
Wu, Y.[Yun],
Zhu, S.Z.[Shun-Zhi],
Multi-Branch Enhanced Discriminative Network for Vehicle
Re-Identification,
ITS(25), No. 2, February 2024, pp. 1263-1274.
IEEE DOI
2402
Feature extraction, Task analysis, Data mining, Pedestrians,
Annotations, Manuals, Vehicle dynamics, Vehicle re-identification,
intelligent transportation systems
BibRef
Huang, J.H.[Jun-Hao],
Deng, Y.H.[Yu-Hui],
Wang, K.[Ke],
Li, Z.W.[Zhang-Wei],
Tang, Z.M.[Zhi-Min],
Ding, W.P.[Wei-Ping],
UnbiasNet: Vehicle Re-Identification Oriented Unbiased Feature
Enhancement by Using Causal Effect,
ITS(25), No. 2, February 2024, pp. 1925-1937.
IEEE DOI
2402
Training, Feature extraction, Computational modeling,
Task analysis, Adaptation models, Benchmark testing, Annotations
BibRef
Li, H.C.[Hong-Chao],
Zheng, A.[Aihua],
Sun, L.P.[Li-Ping],
Luo, Y.[Yonglong],
Camera Topology Graph Guided Vehicle Re-Identification,
MultMed(26), 2024, pp. 1565-1577.
IEEE DOI
2402
Cameras, Topology, Convolutional neural networks, Network topology,
Training, Representation learning, Aggregates,
graph convolutional network
BibRef
Zhao, Q.Q.[Qian-Qian],
Zhan, S.[Simin],
Cheng, R.[Rui],
Zhu, J.Q.[Jian-Qing],
Zeng, H.Q.[Huan-Qiang],
A Benchmark for Vehicle Re-Identification in Mixed Visible and
Infrared Domains,
SPLetters(31), 2024, pp. 726-730.
IEEE DOI
2403
Probes, Protocols, Cameras, Detectors, Training, Benchmark testing,
Residual neural networks, Vehicle re-identification, benchmark
BibRef
Jiao, B.L.[Bing-Liang],
Yang, L.[Lu],
Gao, L.Y.[Li-Ying],
Wang, P.[Peng],
Zhang, S.Z.[Shi-Zhou],
Zhang, Y.N.[Yan-Ning],
Vehicle Re-Identification in Aerial Images and Videos: Dataset and
Approach,
CirSysVideo(34), No. 3, March 2024, pp. 1586-1603.
IEEE DOI Code:
WWW Link.
2403
Autonomous aerial vehicles, Feature extraction, Cameras,
Annotations, Vehicle dynamics, Deformation, Adaptation models,
attention
BibRef
Pang, X.[Xiyu],
Zheng, Y.L.[Yan-Li],
Nie, X.[Xiushan],
Yin, Y.L.[Yi-Long],
Li, X.[Xi],
Multi-axis interactive multidimensional attention network for vehicle
re-identification,
IVC(144), 2024, pp. 104972.
Elsevier DOI
2404
Vehicle re-identification, Attention mechanism, Multi-axis interactive
BibRef
Yu, Z.[Zhi],
Huang, Z.Y.[Zhi-Yong],
Pei, J.[JiaMing],
Tahsin, L.[Lamia],
Sun, D.M.[Da-Ming],
Semantic-Oriented Feature Coupling Transformer for Vehicle
Re-Identification in Intelligent Transportation System,
ITS(25), No. 3, March 2024, pp. 2803-2813.
IEEE DOI
2405
Feature extraction, Transformers, Semantics,
Intelligent transportation systems, Cameras, semantic information
BibRef
Zhao, R.N.[Ruo-Nan],
Yang, L.T.[Laurence T.],
Liu, D.B.[De-Bin],
Zhou, X.K.[Xiao-Kang],
Deng, X.J.[Xian-Jun],
Tang, X.M.[Xue-Ming],
A Multi-Modal Tensor Ring Decomposition for Communication-Efficient
and Trustworthy Federated Learning for ITS in COVID-19 Scenario,
ITS(25), No. 5, May 2024, pp. 3535-3547.
IEEE DOI
2405
COVID-19, Tensors, Data models, Biological system modeling, Training,
Transportation, Data privacy, Intelligent transportation system,
additively homomorphic encryption
BibRef
Wan, Z.J.[Zhi-Jing],
Xu, X.[Xin],
Wang, Z.[Zheng],
Wang, Z.X.[Zhi-Xiang],
Hu, R.M.[Rui-Min],
From Multi-Source Virtual to Real: Effective Virtual Data Search for
Vehicle Re-Identification,
ITS(25), No. 5, May 2024, pp. 3433-3444.
IEEE DOI
2405
Training, Data models, Redundancy, Solid modeling, Pipelines, Engines,
Virtual-to-real vehicle re-identification, data redundancy, data search
BibRef
Sun, C.Y.[Chen-Yang],
Wang, Y.[Yang],
Deng, Y.F.[Yan-Fei],
Li, H.[Huafu],
Zhou, R.D.[Run-Dong],
Guo, J.Q.[Jun-Qi],
Efficient Vehicle-Infrastructure Collaborative Perception Based on
Vehicle Re-Identification and Mini-ICP Algorithm,
ITS(25), No. 7, July 2024, pp. 6580-6593.
IEEE DOI
2407
Feature extraction, Collaboration, Sensors, Bandwidth, Training,
Laser radar, Efficient collaboration, perception fusion,
cooperative vehicle-infrastructure systems (CVIS)
BibRef
Ding, L.[Leqi],
Liu, L.[Lei],
Huang, Y.[Yan],
Li, C.L.[Cheng-Long],
Zhang, C.[Cheng],
Wang, W.[Wei],
Wang, L.[Liang],
Text-to-Image Vehicle Re-Identification: Multi-Scale Multi-View
Cross-Modal Alignment Network and a Unified Benchmark,
ITS(25), No. 7, July 2024, pp. 7673-7686.
IEEE DOI
2407
Task analysis, Feature extraction, Visualization, Training,
Benchmark testing, Trajectory
BibRef
Gong, R.[Rui],
Zhang, X.[Xue],
Pan, J.A.[Jian-An],
Guo, J.[Jie],
Nie, X.[Xiushan],
Vehicle Reidentification Based on Convolution and Vision Transformer
Feature Fusion,
MultMedMag(31), No. 2, April 2024, pp. 61-68.
IEEE DOI
2408
Feature extraction, Transformers, Task analysis,
Multilayer perceptrons, Nonhomogeneous media, Correlation,
Vehicle detection
BibRef
Zhao, Q.Q.[Qian-Qian],
Su, J.J.[Jia-Jun],
Zhu, J.Q.[Jian-Qing],
Liu, L.[Liu],
Zeng, H.Q.[Huan-Qiang],
Modality-Consistent Attention for Visible-Infrared Vehicle
Re-Identification,
SPLetters(31), 2024, pp. 1910-1914.
IEEE DOI
2408
Estimation, Training, Testing, Residual neural networks,
Computer architecture, Cameras, Wheels,
modality-consistent attention
BibRef
Wang, H.[Hai],
Niu, Y.Q.[Ya-Qing],
Chen, L.[Long],
Li, Y.C.[Yi-Cheng],
Sotelo, M.A.[Miguel Angel],
Li, Z.X.[Zhi-Xiong],
Cai, Y.F.[Ying-Feng],
DAIR-V2XReid: A New Real-World Vehicle-Infrastructure Cooperative
Re-ID Dataset and Cross-Shot Feature Aggregation Network Perception
Method,
ITS(25), No. 8, August 2024, pp. 9058-9068.
IEEE DOI
2408
Cameras, Task analysis, Semantics, Feature extraction,
Generative adversarial networks, Collaboration, Training, automatic driving
BibRef
Tao, X.F.[Xue-Feng],
Kong, J.[Jun],
Jiang, M.[Min],
Luo, X.[Xi],
Semantic Camera Self-Aware Contrastive Learning for Unsupervised
Vehicle Re-Identification,
SPLetters(31), 2024, pp. 2175-2179.
IEEE DOI
2409
Cameras, Semantics, Feature extraction, Self-aware, Transformers,
Contrastive learning, Training,
camera self-aware contrastive loss
BibRef
Liu, X.Y.[Xing-Yue],
Qi, J.H.[Jia-Hao],
Chen, C.[Chen],
Bin, K.C.[Kang-Cheng],
Zhong, P.[Ping],
Relation-Aware Weight Sharing in Decoupling Feature Learning Network
for UAV RGB-Infrared Vehicle Re-Identification,
MultMed(26), 2024, pp. 9839-9853.
IEEE DOI
2410
Task analysis, Autonomous aerial vehicles, Feature extraction,
Cameras, Representation learning, Benchmark testing,
vehicle re-identification
BibRef
Wen, Z.[Zaidao],
Wu, J.H.[Jin-Hui],
Lv, Y.F.[Ya-Fei],
Wu, Q.[Qian],
Cross-Modality Vessel Re-Identification With Deep Alignment
Decomposition Network,
MultMed(26), 2024, pp. 10318-10330.
IEEE DOI
2410
Feature extraction, Task analysis, Pedestrians, Surveillance,
Cameras, Benchmark testing, Semantics, deep learning
BibRef
Qiu, M.[Mingkai],
Lu, Y.[Yuhuan],
Li, X.[Xiying],
Lu, Q.[Qiang],
Camera-Aware Differentiated Clustering With Focal Contrastive
Learning for Unsupervised Vehicle Re-Identification,
CirSysVideo(34), No. 10, October 2024, pp. 10121-10134.
IEEE DOI
2411
Cameras, Training, Noise, Task analysis,
Intelligent systems, Unsupervised learning,
focal contrastive learning
BibRef
Sun, W.[Wei],
Hu, Y.[Yahua],
Zhang, X.R.[Xiao-Rui],
Yao, X.[Xin],
He, X.Z.[Xiao-Zheng],
Adversarial Style-Irrelevant Feature Learning With Refined Soft
Pseudo Labels for Domain-Adaptive Vehicle Re-Identification,
ITS(25), No. 12, December 2024, pp. 20602-20615.
IEEE DOI
2412
Feature extraction, Training, Representation learning, Noise,
Adaptation models, Accuracy, Generative adversarial networks,
adversarial learning
BibRef
Zhang, X.[Xin],
Ling, Y.[Yunan],
Li, K.[Kaige],
Shi, W.M.[Wei-Min],
Zhou, Z.[Zhong],
Multimodality Adaptive Transformer and Mutual Learning for
Unsupervised Domain Adaptation Vehicle Re-Identification,
ITS(25), No. 12, December 2024, pp. 20215-20226.
IEEE DOI
2412
Feature extraction, Adaptation models, Transformers, Accuracy,
Data mining, Noise, Data models, Domain adaption,
unsupervised vehicle re-identification
BibRef
Qiu, M.[Mingkai],
Lu, Y.[Yuhuan],
Li, X.[Xiying],
Lu, Q.[Qiang],
Inter-Intra Cluster Reorganization for Unsupervised Vehicle
Re-Identification,
ITS(25), No. 12, December 2024, pp. 20493-20507.
IEEE DOI
2412
Reliability, Contrastive learning, Cameras, Training,
Reliability engineering, Adaptation models, Noise, Visualization,
cluster reorganization
BibRef
Wang, Z.F.[Zhao-Fa],
Wang, L.Y.[Li-Yang],
Shi, Z.P.[Zhi-Ping],
Zhang, M.M.[Miao-Miao],
Geng, Q.[Qichuan],
Jiang, N.[Na],
A survey on person and vehicle re-identification,
IET-CV(18), No. 8, 2024, pp. 1235-1268.
DOI Link
2501
Survey, Re-Identification. image retrieval
BibRef
Hu, Z.J.[Zhi-Jun],
Su, Y.[You],
Raj, R.S.P.[Raja Soosaimarian Peter],
Cheng, X.J.[Xian-Jing],
Zhang, Z.[Zaijun],
View-Aware-Based Post-Processing for Vehicle Re-Identification,
ITS(26), No. 1, January 2025, pp. 849-864.
IEEE DOI
2501
Training, Probes, Testing, Mathematical models, Feature extraction,
Automobiles, Measurement, Image coding, Deep learning, post-processing
BibRef
Kamenou, E.[Eleni],
del Rincón, J.M.[Jesús Martínez],
Miller, P.[Paul],
Devlin-Hill, P.[Patricia],
A Meta-learning Approach for Domain Generalisation across Visual
Modalities in Vehicle Re-identification,
PBVS23(385-393)
IEEE DOI
2309
BibRef
Moral, P.[Paula],
García-Martín, Á.[Álvaro],
Martínez, J.M.[José M.],
Vehicle Re-identification Based on Unsupervised Domain Adaptation by
Incremental Generation of Pseudo-labels,
CIARP23(I:76-89).
Springer DOI
2312
BibRef
Khorramshahi, P.[Pirazh],
Shenoy, V.[Vineet],
Chellappa, R.[Rama],
Robust and Scalable Vehicle Re-Identification via Self-Supervision,
AICity23(5295-5304)
IEEE DOI
2309
BibRef
Piano, L.[Luca],
Pratticň, F.G.[Filippo Gabriele],
Russo, A.S.[Alessandro Sebastian],
Lanari, L.[Lorenzo],
Morra, L.[Lia],
Lamberti, F.[Fabrizio],
Bent and Broken Bicycles: Leveraging synthetic data for damaged
object re-identification,
WACV23(4870-4880)
IEEE DOI
2302
Image segmentation, Computational modeling, Image retrieval,
Bicycles, keywords instance-level retrieval, re-identification, transformers
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.B.[Jing-Bo],
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
BibRef
Liu, C.[Chong],
Zhang, Y.Q.[Yu-Qi],
Luo, H.[Hao],
Tang, J.S.[Jia-Sheng],
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.Q.[Yu-Qi],
Liu, C.[Chong],
Jiang, Y.Q.[Yi-Qi],
He, S.T.[Shu-Ting],
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Training, Computational modeling,
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Huynh, S.V.[Su V.],
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AICity21(4142-4149)
IEEE DOI
2109
Training, Target tracking, Head, Urban areas, Stacking
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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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ICPR21(9099-9106)
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2105
Measurement, Space vehicles, Deep learning, Annotations,
System performance, Cameras
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Xu, Z.M.[Zhe-Ming],
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Learning Matching Behavior Differences for Compressing Vehicle
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VCIP20(523-526)
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Training, Testing, Probes, Image coding, Loss measurement,
Computational modeling, Trajectory, Deep Learning,
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Khorramshahi, P.[Pirazh],
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Chen, T.S.[Tsai-Shien],
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2011
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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)
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2008
Adaptation models, Feature extraction, Task analysis, Training,
Data models, Image color analysis, Urban areas
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Meng, D.,
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Gao, X.,
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Huang, Q.,
Parsing-Based View-Aware Embedding Network for Vehicle
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CVPR20(7101-7110)
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2008
Feature extraction, Task analysis, Cameras,
Training, Image color analysis, Fuses
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Chen, T.,
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Chien, S.,
Viewpoint-aware Channel-wise Attentive Network for Vehicle
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City20(2448-2455)
IEEE DOI
2008
Feature extraction, Estimation, Cameras, Task analysis, Semantics,
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Fernández, M.[Marta],
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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.
Feature extraction, Cameras, Trajectory, Task analysis, Training,
Urban areas, Servers
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Zhu, X.,
Luo, Z.,
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Ji, X.,
VOC-RelD: Vehicle Re-identification based on
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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.,
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Zhang, M.,
Zhang, Y.,
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Jiang, W.,
Multi-Domain Learning and Identity Mining for Vehicle
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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
Re-identification,
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
2008
Feature extraction, Training, Image color analysis, Robustness,
Cameras, Task analysis, Automobiles
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Chu, R.H.[Rui-Hang],
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Li, Y.D.[Ya-Dong],
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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.,
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
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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
2004
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
BibRef
Wu, M.J.[Ming-Jie],
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2003
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Lou, Y.H.[Yi-Hang],
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VERI-Wild: A Large Dataset and a New Method for Vehicle
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2002
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Yang, X.,
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Vehicle Re-Identification by Multi-Grain Learni,
ICIP19(3113-3117)
IEEE DOI
1910
Vehicle re-identification, Multi-grain ranking loss
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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
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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)
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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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MMMod19(II:426-439).
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1901
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Wu, F.,
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Joint Semi-supervised Learning and Re-ranking for Vehicle
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ICPR18(278-283)
IEEE DOI
1812
Training, Probes, Feature extraction, Semisupervised learning,
Generative adversarial networks, Smoothing methods, Cameras
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Marín-Reyes, P.A.,
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Unsupervised Vehicle Re-identification Using Triplet Networks,
City18(166-1665)
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1812
Videos, Urban areas, Task analysis, Artificial intelligence,
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Porrello, A.[Angelo],
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Code, Re-Identification.
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Li, S.,
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Vehicle Re-Identification by Deep Feature Fusion Based on Joint
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ICPR18(2032-2037)
IEEE DOI
1812
Feature extraction, Bayes methods, Fuses, Licenses, Training,
Training data, Task analysis
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Zhu, J.,
Zeng, H.,
Lei, Z.,
Liao, S.,
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A Shortly and Densely Connected Convolutional Neural Network for
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ICPR18(3285-3290)
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Convolutional neural networks, Linear programming,
Feature extraction, Training, Cameras, Surveillance
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Wu, C.,
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Vehicle Re-identification with the Space-Time Prior,
City18(121-1217)
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1812
Feature extraction, Videos, Automobiles, Task analysis, Urban areas,
Visualization, Testing
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Jiang, N.,
Xu, Y.,
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Wu, W.,
Multi-Attribute Driven Vehicle Re-Identification with
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ICIP18(858-862)
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Feature extraction, Image color analysis,
Machine learning, Probes, Lighting, Cameras,
spatial-temporal re-ranking
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Kanaci, A.[Aytaç],
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Cui, C.,
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Vehicle re-identification by fusing multiple deep neural networks,
IPTA17(1-6)
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1804
convolution, feature extraction, feedforward neural nets,
image classification, image colour analysis, image fusion,
Vehicle re-identification
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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
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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
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ICIP17(395-399)
IEEE DOI
1803
Computational modeling, Face recognition, Feature extraction,
Image recognition, Machine learning, Task analysis, Training,
Vehicle Retrieval
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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
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Wang, Z.,
Tang, L.,
Liu, X.,
Yao, Z.,
Yi, S.,
Shao, J.,
Yan, J.,
Wang, S.,
Li, H.,
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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
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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
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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 .