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convolutional neural nets, learning (artificial intelligence),
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Object tracking
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IET-CV(7), No. 5, October 2013, pp. 320-334.
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1512
BibRef
Earlier: A1, A2, A3, Only:
Multi-cue Visual Tracking Using Robust Feature-Level Fusion Based on
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CVPR14(1194-1201)
IEEE DOI
1409
feature extraction
BibRef
Wang, L.J.[Li-Jun],
Lu, H.C.[Hu-Chuan],
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Visual Tracking via Structure Constrained Grouping,
SPLetters(22), No. 7, July 2015, pp. 794-798.
IEEE DOI
1412
image representation
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CVPR16(1373-1381)
IEEE DOI
1612
BibRef
Earlier:
Visual Tracking with Fully Convolutional Networks,
ICCV15(3119-3127)
IEEE DOI
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Feature extraction
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1504
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1703
Dictionaries
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1802
image representation, learning (artificial intelligence),
object tracking, video signal processing, appearance modeling,
sparse representation
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Zhang, S.,
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ITS(19), No. 1, January 2018, pp. 187-198.
IEEE DOI
1801
Feature extraction, Manifolds, Target tracking, Training,
Visualization, Metric learning, point to set, visual tracking
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Wang, S.F.[Shao-Fei],
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Learning Optimal Parameters for Multi-target Tracking with Contextual
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1704
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Earlier:
Learning Optimal Parameters For Multi-target Tracking,
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Multi-object tracking through learning relational appearance features
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1710
Multi-object tracking
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1712
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Zhou, H.,
Ouyang, W.,
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Deep Continuous Conditional Random Fields With Asymmetric
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CirSysVideo(29), No. 4, April 2019, pp. 1011-1022.
IEEE DOI
1904
Tracking, Trajectory, Visualization, Neural networks,
Machine learning, Mathematical model, Feature extraction,
asymmetric pairwise terms
BibRef
Chen, L.,
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Chen, R.,
Zhuang, Z.,
Aggregate Tracklet Appearance Features for Multi-Object Tracking,
SPLetters(26), No. 11, November 2019, pp. 1613-1617.
IEEE DOI
1911
convolutional neural nets, feature extraction,
image representation, object detection, object tracking,
spatial-temporal attention
BibRef
Kang, B.[Bin],
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Liang, D.[Dong],
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PR(88), 2019, pp. 75-89.
Elsevier DOI
1901
Sparse representation, Visual tracking, Multi-view learning,
Dual group structure
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Lan, L.,
Wang, X.,
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Tao, D.,
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Huang, T.S.,
Interacting Tracklets for Multi-Object Tracking,
IP(27), No. 9, September 2018, pp. 4585-4597.
IEEE DOI
1807
Boolean functions, image motion analysis,
learning (artificial intelligence), object detection,
tracklets
BibRef
Wang, J.,
Guo, Y.,
Tang, X.,
Hu, Q.,
An, W.,
Semi-Online Multiple Object Tracking Using Graphical Tracklet
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SPLetters(25), No. 11, November 2018, pp. 1725-1729.
IEEE DOI
1811
graph theory, learning (artificial intelligence), minimisation,
object tracking, graphical tracklet association,
tracklet association
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Yang, T.[Tao],
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Online multi-object tracking combining optical flow and compressive
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JVCIR(58), 2019, pp. 178-186.
Elsevier DOI
1901
BibRef
Earlier:
Multi-object Tracking Using Compressive Sensing Features in Markov
Decision Process,
ACIVS17(505-517).
Springer DOI
1712
Multi-object tracking, Markov decision process,
Tracking-learning-detection, Compressive sensing features
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Makhura, O.J.[Onalenna J.],
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Learn-select-track: An approach to multi-object tracking,
SP:IC(74), 2019, pp. 153-161.
Elsevier DOI
1904
Multi-object tracking, Object colours,
Density-based clustering, Low level local features
BibRef
Liu, M.J.[Ming-Jie],
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Yang, B.[Bin],
Cui, X.N.[Xue-Nan],
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Online multiple object tracking using confidence score-based appearance
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IET-CV(13), No. 3, April 2019, pp. 312-318.
DOI Link
1904
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Mhalla, A.[Ala],
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Spatio-temporal object detection by deep learning:
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IVC(88), 2019, pp. 120-131.
Elsevier DOI
1908
Multi-object tracking,
Interlacing and inverse interlacing models, Specialization,
Interlaced deep detector
BibRef
Yu, H.Y.[Hong-Yang],
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Su, L.[Li],
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Conditional GAN based individual and global motion fusion for
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Elsevier DOI
2004
Multi-object tracking, Neural networks, UAV
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Zhang, X.C.[Xing-Chen],
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DSiamMFT: An RGB-T fusion tracking method via dynamic Siamese
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SP:IC(84), 2020, pp. 115756.
Elsevier DOI
2004
Object tracking, RGB-T fusion tracking,
Dynamic Siamese networks, Deep learning, Image fusion
BibRef
Li, P.X.[Pei-Xia],
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Lu, H.C.[Hu-Chuan],
Visual tracking by dynamic matching-classification network switching,
PR(107), 2020, pp. 107419.
Elsevier DOI
2008
Visual Tracking, Deep Learning, Ensemble learning
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Sharma, A.[Anil],
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Intelligent querying for target tracking in camera networks using
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IVC(103), 2020, pp. 104022.
Elsevier DOI
2011
Camera networks, Deep reinforcement learning, Target tracking,
Multi-camera tracking 2010 MSC: 00-01, 99-00
BibRef
Chuang, T.Y.[Tzu-Yi],
Han, J.Y.[Jen-Yu],
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RS(12), No. 12, 2020, pp. xx-yy.
DOI Link
2006
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Emami, P.[Patrick],
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Machine Learning Methods for Data Association in Multi-Object
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Surveys(53), No. 4, August 2020, pp. xx-yy.
DOI Link
2010
deep learning, machine learning, Multi-object tracking, data association
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Sun, S.J.[Shi-Jie],
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Deep Affinity Network for Multiple Object Tracking,
PAMI(43), No. 1, January 2021, pp. 104-119.
IEEE DOI
2012
Object tracking, Computational modeling, Deep learning, Detectors,
Target tracking, Feature extraction, Multiple object tracking,
on-line tracking
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Ma, C.[Cong],
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Li, Y.[Yuan],
Jia, H.Z.[Hui-Zhu],
Xie, X.D.[Xiao-Dong],
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Deep Human-Interaction and Association by Graph-Based Learning for
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IJCV(129), No. 6, June 2021, pp. 1993-2010.
2106
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Ma, C.[Cong],
Yang, F.[Fan],
Li, Y.[Yuan],
Jia, H.Z.[Hui-Zhu],
Xie, X.D.[Xiao-Dong],
Gao, W.[Wen],
Deep Trajectory Post-Processing and Position Projection for Single &
Multiple Camera Multiple Object Tracking,
IJCV(129), No. 12, December 2021, pp. 3255-3278.
Springer DOI
2111
BibRef
Liu, Q.[Qiao],
Li, X.[Xin],
He, Z.Y.[Zhen-Yu],
Fan, N.[Nana],
Yuan, D.[Di],
Wang, H.P.[Hong-Peng],
Learning Deep Multi-Level Similarity for Thermal Infrared Object
Tracking,
MultMed(23), 2021, pp. 2114-2126.
IEEE DOI
2107
Object tracking, Semantics, Training, Task analysis,
Adaptation models, Correlation, Feature extraction, Thermal infrared dataset
BibRef
Liu, Q.[Qiao],
Yuan, D.[Di],
Fan, N.[Nana],
Gao, P.[Peng],
Li, X.[Xin],
He, Z.Y.[Zhen-Yu],
Learning Dual-Level Deep Representation for Thermal Infrared Tracking,
MultMed(25), 2023, pp. 1269-1281.
IEEE DOI
2305
Object tracking, Biological system modeling, Task analysis,
Correlation, Multitasking, Adaptation models, Feature extraction,
Thermal infrared dataset
BibRef
Jiang, B.[Bo],
Zhang, Y.[Yuan],
Luo, B.[Bin],
Cao, X.C.[Xiao-Chun],
Tang, J.[Jin],
STGL: Spatial-Temporal Graph Representation and Learning for Visual
Tracking,
MultMed(23), 2021, pp. 2162-2171.
IEEE DOI
2107
Target tracking, Computational modeling, Visualization,
Noise measurement, Semisupervised learning, Shape, graph learning
BibRef
Wan, X.Y.[Xing-Yu],
Cao, J.[Jiakai],
Zhou, S.P.[San-Ping],
Wang, J.J.[Jin-Jun],
Zheng, N.N.[Nan-Ning],
Tracking Beyond Detection:
Learning a Global Response Map for End-to-End Multi-Object Tracking,
IP(30), 2021, pp. 8222-8235.
IEEE DOI
2110
Trajectory, Target tracking, Object detection, Measurement,
Task analysis, Feature extraction, Data models,
deep neural network
BibRef
Tu, Z.Z.[Zheng-Zheng],
Lin, C.[Chun],
Zhao, W.[Wei],
Li, C.L.[Cheng-Long],
Tang, J.[Jin],
M5L: Multi-Modal Multi-Margin Metric Learning for RGBT Tracking,
IP(31), 2022, pp. 85-98.
IEEE DOI
2112
Measurement, Robustness, Feature extraction, Fuses, Collaboration,
Visualization, Task analysis, Deep metric learning,
RGBT tracking
BibRef
Li, S.W.[Sheng-Wu],
Zhang, X.[Xuande],
Xiong, J.[Jing],
Ning, C.J.[Chen-Jing],
Zhang, M.[Mingke],
Learning spatial self-attention information for visual tracking,
IET-IPR(16), No. 1, 2022, pp. 49-60.
DOI Link
2112
BibRef
Chen, Z.Z.[Zhong-Ze],
Li, J.[Jing],
Wu, J.[Jia],
Chang, J.[Jun],
Xiao, Y.[Yafu],
Wang, X.T.[Xiao-Ting],
Drift-Proof Tracking With Deep Reinforcement Learning,
MultMed(24), 2022, pp. 609-624.
IEEE DOI
2202
Target tracking, Reinforcement learning, Training, Robustness,
Object tracking, Measurement, Real-time systems, Object tracking,
drift problems
BibRef
Li, X.J.[Xiao-Jing],
Huang, L.[Lei],
Wei, Z.Q.[Zhi-Qiang],
A Twofold Convolutional Regression Tracking Network With Temporal and
Spatial Mechanism,
CirSysVideo(32), No. 3, March 2022, pp. 1537-1551.
IEEE DOI
2203
Target tracking, Feature extraction, Visualization, Training,
Correlation, Task analysis, Semantics, Visual tracking,
spatial and temporal mechanism
BibRef
Brasó, G.[Guillem],
Cetintas, O.[Orcun],
Leal-Taixé, L.[Laura],
Multi-Object Tracking and Segmentation Via Neural Message Passing,
IJCV(130), No. 12, December 2022, pp. 3035-3053.
Springer DOI
2211
BibRef
Ye, L.L.[Liang-Ling],
Li, W.[Weida],
Zheng, L.X.[Li-Xin],
Zeng, Y.Y.[Yuan-Yue],
Lightweight and Deep Appearance Embedding for Multiple Object
Tracking,
IET-CV(16), No. 6, 2022, pp. 489-503.
DOI Link
2208
BibRef
Saada, M.[Mohamad],
Kouppas, C.[Christos],
Li, B.H.[Bai-Hua],
Meng, Q.G.[Qing-Gang],
A multi-object tracker using dynamic Bayesian networks and a residual
neural network based similarity estimator,
CVIU(225), 2022, pp. 103569.
Elsevier DOI
2212
Multi-object tracking, Dynamic Bayesian networks,
Residual neural networks, YOLO V5, MOTChallenge
BibRef
Wang, M.[Mianzhao],
Shi, F.[Fan],
Zhao, M.[Meng],
Jia, C.[Chen],
Tian, W.W.[Wei-Wei],
He, T.[Tian],
Fu, Y.[Yu],
Cheng, X.[Xu],
An Online Multiobject Tracking Network for Autonomous Driving in
Areas Facing Epidemic,
ITS(23), No. 12, December 2022, pp. 25191-25200.
IEEE DOI
2212
Feature extraction, Correlation, Target tracking, Strain, Epidemics,
Aggregates, Detectors, Multi-object tracking, epidemic areas, re-ID embedding
BibRef
Zheng, Y.J.[Ya-Jing],
Yu, Z.F.[Zhao-Fei],
Wang, S.[Song],
Huang, T.J.[Tie-Jun],
Spike-Based Motion Estimation for Object Tracking Through
Bio-Inspired Unsupervised Learning,
IP(32), 2023, pp. 335-349.
IEEE DOI
2301
Cameras, Tracking, Neuromorphics, Vision sensors, Neurons,
Motion estimation, Target tracking, Neuromorphic vision sensor,
high-speed object tracking
BibRef
Li, R.[Rui],
Zhang, B.[Baopeng],
Liu, J.[Jun],
Liu, W.[Wei],
Teng, Z.[Zhu],
Inference-Domain Network Evolution: A New Perspective for One-Shot
Multi-Object Tracking,
IP(32), 2023, pp. 2147-2159.
IEEE DOI
2304
Task analysis, Feature extraction, Noise measurement, Cameras,
Adaptation models, Annotations, data association
BibRef
Nalaie, K.[Keivan],
Zheng, R.[Rong],
AttTrack: Online Deep Attention Transfer for Multi-object Tracking,
WACV23(1654-1663)
IEEE DOI
2302
Training, Representation learning, Knowledge engineering,
Degradation, Visual analytics, Surveillance, Object detection
BibRef
Chen, X.[Xi],
Zhang, Y.F.[Yi-Feng],
Multi-Object Tracking Based on Deep Path Aggregation Network,
ICIVC22(214-221)
IEEE DOI
2301
Location awareness, Target tracking, Object detection,
Feature extraction, Real-time systems, Object tracking, real-time
BibRef
Zhao, S.Y.[Shuang-Ye],
Wu, Y.[Yubin],
Wang, S.[Shuai],
Ke, W.[Wei],
Sheng, H.[Hao],
Mask Guided Spatial-Temporal Fusion Network for Multiple Object
Tracking,
ICIP22(3231-3235)
IEEE DOI
2211
Target tracking, Neural networks, Feature extraction, Reliability,
Object tracking, Multi-object tracking, tracking by detection,
mask guided network
BibRef
Pi, Z.X.[Zhi-Xiong],
Wan, W.T.[Wei-Tao],
Sun, C.[Chong],
Gao, C.X.[Chang-Xin],
Sang, N.[Nong],
Li, C.[Chen],
Hierarchical Feature Embedding for Visual Tracking,
ECCV22(XXII:428-445).
Springer DOI
2211
WWW Link.
BibRef
Song, L.C.[Liang-Chen],
Gong, X.[Xuan],
Planche, B.[Benjamin],
Zheng, M.[Meng],
Doermann, D.[David],
Yuan, J.S.[Jun-Song],
Chen, T.[Terrence],
Wu, Z.Y.[Zi-Yan],
PREF: Predictability Regularized Neural Motion Fields,
ECCV22(XXII:664-681).
Springer DOI
2211
BibRef
Yu, S.Z.[Shu-Zhi],
Wu, G.H.[Guan-Hang],
Gu, C.H.[Chun-Hui],
Fathy, M.E.[Mohammed E.],
TDT: Teaching Detectors to Track without Fully Annotated Videos,
L3D-IVU22(3939-3949)
IEEE DOI
2210
Training, Annotations, Detectors, Predictive models, Benchmark testing
BibRef
He, J.W.[Jia-Wei],
Huang, Z.[Zehao],
Wang, N.Y.[Nai-Yan],
Zhang, Z.X.[Zhao-Xiang],
Learnable Graph Matching: Incorporating Graph Partitioning with Deep
Feature Learning for Multiple Object Tracking,
CVPR21(5295-5305)
IEEE DOI
2111
Training, Deep learning, Image edge detection, Neural networks,
Feature extraction, Object tracking, Quadratic programming
BibRef
Wu, J.L.[Jia-Lian],
Cao, J.L.[Jia-Le],
Song, L.C.[Liang-Chen],
Wang, Y.[Yu],
Yang, M.[Ming],
Yuan, J.S.[Jun-Song],
Track to Detect and Segment: An Online Multi-Object Tracker,
CVPR21(12347-12356)
IEEE DOI
2111
Solid modeling, Costs, Tracking,
Motion segmentation, Neural networks, Object detection
BibRef
Zhang, Z.P.[Zhi-Peng],
Liu, Y.H.[Yi-Hao],
Wang, X.[Xiao],
Li, B.[Bing],
Hu, W.M.[Wei-Ming],
Learn to Match: Automatic Matching Network Design for Visual Tracking,
ICCV21(13319-13328)
IEEE DOI
2203
Training, Degradation, Visualization, Codes, Statistical analysis,
Oceans, Motion and tracking,
BibRef
Zheng, J.[Jilai],
Ma, C.[Chao],
Peng, H.[Houwen],
Yang, X.K.[Xiao-Kang],
Learning to Track Objects from Unlabeled Videos,
ICCV21(13526-13535)
IEEE DOI
2203
Training, Codes, Dynamic programming, Object recognition,
Unsupervised learning, Optical flow, Motion and tracking,
BibRef
Xie, F.[Fei],
Wang, C.Y.[Chun-Yu],
Wang, G.[Guangting],
Yang, W.K.[Wan-Kou],
Zeng, W.J.[Wen-Jun],
Learning Tracking Representations via Dual-Branch Fully Transformer
Networks,
VOT21(2688-2697)
IEEE DOI
2112
Target tracking, Costs, Fuses, Computational modeling,
Graphics processing units, Transformers, Feature extraction
BibRef
Liu, C.X.[Cheng-Xin],
Cao, Z.G.[Zhi-Guo],
Li, W.[Wei],
Xiao, Y.[Yang],
Du, S.[Shuaiyuan],
Zhu, A.[Angfan],
Exploiting Distilled Learning for Deep Siamese Tracking,
ICPR21(577-583)
IEEE DOI
2105
Power demand, Pipelines, Memory management, Benchmark testing,
Mobile handsets, Pattern recognition
BibRef
Dai, P.[Peng],
Weng, R.L.[Ren-Liang],
Choi, W.[Wongun],
Zhang, C.S.[Chang-Shui],
He, Z.P.[Zhang-Ping],
Ding, W.[Wei],
Learning a Proposal Classifier for Multiple Object Tracking,
CVPR21(2443-2452)
IEEE DOI
2111
Deep learning, Detectors, Market research,
Trajectory, Computational efficiency, Proposals
BibRef
Xu, Y.,
sep, A.,
Ban, Y.,
Horaud, R.,
Leal-Taixé, L.,
Alameda-Pineda, X.,
How to Train Your Deep Multi-Object Tracker,
CVPR20(6786-6795)
IEEE DOI
2008
Loss measurement, Training, Standards, Target tracking,
Optimization, Neural networks
BibRef
Li, Z.,
Xiong, F.,
Zhou, J.,
Wang, J.,
Lu, J.,
Qian, Y.,
BAE-Net: A Band Attention Aware Ensemble Network for Hyperspectral
Object Tracking,
ICIP20(2106-2110)
IEEE DOI
2011
Videos, Hyperspectral imaging, Target tracking,
Image color analysis, Object tracking, Machine learning, Color,
ensemble learning
BibRef
Zhang, D.,
Zheng, Z.,
High Performance Visual Tracking With Siamese Actor-Critic Network,
ICIP20(2116-2120)
IEEE DOI
2011
Training, Feature extraction, Visualization, Real-time systems,
Learning (artificial intelligence), Target tracking, Robustness,
Object Tracking
BibRef
Wang, J.,
Wang, Y.,
Zhang, S.,
Xu, C.,
Deng, C.,
Dictionary Learning for Visual Tracking with Dimensionality Reduction,
ICIVC20(251-255)
IEEE DOI
2009
Target tracking, Visualization, Dictionaries, Robustness,
Video sequences, Training, Appearance variation, Visual tracking,
Target representation
BibRef
Harley, A.W.[Adam W.],
Lakshmikanth, S.K.[Shrinidhi Kowshika],
Schydlo, P.[Paul],
Fragkiadaki, K.[Katerina],
Tracking Emerges by Looking Around Static Scenes, with Neural 3d
Mapping,
ECCV20(XXVI:598-614).
Springer DOI
2011
BibRef
Jin, J.T.[Jia-Ting],
Li, X.W.[Xing-Wei],
Li, X.L.[Xin-Long],
Guan, S.J.[Shao-Jie],
Online Multi-object Tracking with Siamese Network and Optical Flow,
ICIVC20(193-198)
IEEE DOI
2009
Kalman filters, Feature extraction, Optical flow, Trajectory,
Target tracking, Multi-object tracking, Siamese Network,
DeepSORT
BibRef
Weng, X.,
Wang, Y.,
Man, Y.,
Kitani, K.M.,
GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking With
2D-3D Multi-Feature Learning,
CVPR20(6498-6507)
IEEE DOI
2008
Feature extraction,
Tracking, Neural networks, Pipelines, Training
BibRef
Voigtlaender, P.,
Luiten, J.,
Torr, P.H.S.,
Leibe, B.,
Siam R-CNN: Visual Tracking by Re-Detection,
CVPR20(6577-6587)
IEEE DOI
2008
Heuristic algorithms, Feature extraction, Target tracking, Head,
Benchmark testing, Dynamic programming
BibRef
Brasó, G.,
Leal-Taixé, L.,
Learning a Neural Solver for Multiple Object Tracking,
CVPR20(6246-6256)
IEEE DOI
2008
Trajectory, Image edge detection, Task analysis, Message passing,
Object tracking, Optimization, Object detection
BibRef
Ruiz, I.[Idoia],
Porzi, L.[Lorenzo],
Bulò, S.R.[Samuel Rota],
Kontschieder, P.[Peter],
Serrat, J.[Joan],
Weakly Supervised Multi-Object Tracking and Segmentation,
WACVW21(125-133) Autonomous Vehicle Vision
IEEE DOI
2105
Training, Location awareness, Heating systems, Measurement,
Image edge detection, Benchmark testing
BibRef
Porzi, L.[Lorenzo],
Hofinger, M.,
Ruiz, I.[Idoia],
Serrat, J.[Joan],
Bulò, S.R.[Samuel Rota],
Kontschieder, P.[Peter],
Learning Multi-Object Tracking and Segmentation From Automatic
Annotations,
CVPR20(6845-6854)
IEEE DOI
2008
Videos, Training data, Task analysis, Image segmentation, Pipelines,
Optical imaging, Semantics
BibRef
Ardö, H.,
Nilsson, M.,
Multi Target Tracking from Drones by Learning from Generalized Graph
Differences,
VisDrone19(46-54)
IEEE DOI
2004
autonomous aerial vehicles, graph theory,
learning (artificial intelligence), object detection,
Multi target tracking
BibRef
He, Z.[Zhen],
Li, J.[Jian],
Liu, D.[Daxue],
He, H.[Hangen],
Barber, D.[David],
Tracking by Animation: Unsupervised Learning of Multi-Object Attentive
Trackers,
CVPR19(1318-1327).
IEEE DOI
2002
BibRef
Maksai, A.[Andrii],
Fua, P.[Pascal],
Eliminating Exposure Bias and Metric Mismatch in Multiple Object
Tracking,
CVPR19(4634-4643).
IEEE DOI
2002
BibRef
Emambakhsh, M.[Mehryar],
Bay, A.[Alessandro],
Vazquez, E.[Eduard],
Deep Recurrent Neural Network for Multi-target Filtering,
MMMod19(II:519-531).
Springer DOI
1901
Results:
WWW Link.
BibRef
Manh, H.,
Alaghband, G.,
Spatiotemporal KSVD Dictionary Learning for Online Multi-target
Tracking,
CRV18(150-157)
IEEE DOI
1812
Dictionaries, Sparse matrices, Robots, Video sequences,
Feature extraction, Color, multi-target tracking,
online appearance learning
BibRef
Ren, L.L.[Liang-Liang],
Lu, J.W.[Ji-Wen],
Wang, Z.F.[Zi-Feng],
Tian, Q.[Qi],
Zhou, J.[Jie],
Collaborative Deep Reinforcement Learning for Multi-object Tracking,
ECCV18(III: 605-621).
Springer DOI
1810
BibRef
Wan, X.,
Wang, J.,
Zhou, S.,
An Online and Flexible Multi-object Tracking Framework Using Long
Short-Term Memory,
PBVS18(1311-13118)
IEEE DOI
1812
Trajectory, Tracking, Computational modeling, Kalman filters,
Optical flow, Logic gates
BibRef
Wan, X.,
Wang, J.,
Kong, Z.,
Zhao, Q.,
Deng, S.,
Multi-Object Tracking Using Online Metric Learning with Long
Short-Term Memory,
ICIP18(788-792)
IEEE DOI
1809
Trajectory, Target tracking, Computational modeling,
Kalman filters, Optical flow, Multiple Object Tracking,
Data Association
BibRef
Ullah, M.,
Alaya Cheikh, F.,
Deep Feature Based End-to-End Transportation Network for Multi-Target
Tracking,
ICIP18(3738-3742)
IEEE DOI
1809
Target tracking, Trajectory, Optimization, Transportation,
Dynamic programming, Feature extraction, Transportation network,
multi-target tracking
BibRef
Cui, Y.W.[Ya-Wen],
Zhang, B.[Bo],
Yang, W.J.[Wen-Jing],
Wang, Z.Y.[Zhi-Yuan],
Li, Y.[Yin],
Yi, X.D.[Xiao-Dong],
Tang, Y.H.[Yu-Hua],
End-to-End Visual Target Tracking in Multi-Robot Systems Based on
Deep Convolutional Neural Network,
CEFR-LCV17(1113-1121)
IEEE DOI
1802
Angular velocity, Cameras, Feature extraction,
Robot vision systems, Target tracking
BibRef
Anh, N.T.L.,
Khan, F.M.,
Negin, F.,
Bremond, F.,
Multi-Object tracking using multi-channel part appearance
representation,
AVSS17(1-6)
IEEE DOI
1806
Gaussian processes, feature extraction, image representation,
learning (artificial intelligence), object detection,
Trajectory
BibRef
Gaidon, A.[Adrien],
Wang, Q.[Qiao],
Cabon, Y.[Yohann],
Vig, E.[Eleonora],
VirtualWorlds as Proxy for Multi-object Tracking Analysis,
CVPR16(4340-4349)
IEEE DOI
1612
Learning, synthetic data.
BibRef
Kieritz, H.,
Hübner, W.,
Arens, M.,
Joint Detection and Online Multi-object Tracking,
Joint18(1540-15408)
IEEE DOI
1812
Detectors, Recurrent neural networks, History, Object tracking,
Feature extraction, Multilayer perceptrons
BibRef
Sadeghian, A.,
Alahi, A.,
Savarese, S.,
Tracking the Untrackable:
Learning to Track Multiple Cues with Long-Term Dependencies,
ICCV17(300-311)
IEEE DOI
1802
learning (artificial intelligence), object detection,
recurrent neural nets, sensor fusion, target tracking,
Trajectory
BibRef
Risse, B.,
Mangan, M.,
Webb, B.,
Pero, L.D.,
Visual Tracking of Small Animals in Cluttered Natural Environments
Using a Freely Moving Camera,
Wildlife17(2840-2849)
IEEE DOI
1802
Animals, Cameras, Optimization, Target tracking,
Visualization
BibRef
Schulter, S.,
Vernaza, P.,
Choi, W.,
Chandraker, M.,
Deep Network Flow for Multi-object Tracking,
CVPR17(2730-2739)
IEEE DOI
1711
Bipartite graph, Cost function, Image edge detection,
Neural networks, Trajectory
BibRef
Dimou, A.,
Medentzidou, P.,
Álvarez García, F.,
Daras, P.,
Multi-target detection in CCTV footage for tracking applications
using deep learning techniques,
ICIP16(928-932)
IEEE DOI
1610
Cameras
BibRef
Chau, D.P.[Duc Phu],
Subramanian, K.,
Brémond, F.[François],
Adaptive Neuro-Fuzzy Controller for Multi-object Tracker,
CVS15(466-476).
Springer DOI
1507
BibRef
Luo, W.H.[Wen-Han],
Kim, T.K.[Tae-Kyun],
Stenger, B.[Bjorn],
Zhao, X.W.[Xiao-Wei],
Cipolla, R.[Roberto],
Bi-label Propagation for Generic Multiple Object Tracking,
CVPR14(1290-1297)
IEEE DOI
1409
Multiple object tracking;clustered multi-task learning
BibRef
Yan, W.[Wang],
Han, X.Y.[Xiao-Ye],
Pavlovic, V.[Vladimir],
Structured Learning for Multiple Object Tracking,
BMVC12(48).
DOI Link
1301
BibRef
Li, M.[Min],
Chen, W.[Wei],
Huang, K.Q.[Kai-Qi],
Tan, T.N.[Tie-Niu],
Multi-Target Tracking by Learning Class-Specific and Instance-Specific
Cues,
ACCV10(II: 67-81).
Springer DOI
1011
BibRef
Yuan, X.T.[Xiao-Tong],
Li, S.Z.,
Learning Feature Extraction and Classification for Tracking Multiple
Objects: A Unified Framework,
AVSBS06(22-22).
IEEE DOI
0611
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Online Tracking, Real Time Tracking Multiple Objects .