16.6.2.3 Tracking using Neural Nets, Learning

Anguita, D., Parodi, G., Zunino, R.,
Neural Structures for Visual-Motion Tracking,
MVA(8), No. 5, 1995, pp. 275-288.
Springer DOI BibRef 9500

Agarwal, A.[Abhinav], Datla, S.[Sanketh], Tyagi, B.[Barjeev], Niyogi, R.[Rajdeep],
Novel design for real time path tracking with computer vision using neural networks,
IJCVR(1), No. 4, 2010, pp. 380-391.
DOI Link 1102
BibRef

Mei, X.[Xue], Ling, H.B.[Hai-Bin],
Robust Visual Tracking and Vehicle Classification via Sparse Representation,
PAMI(33), No. 11, November 2011, pp. 2259-2272.
IEEE DOI 1110
BibRef
Earlier:
Robust Visual Tracking Using L1 Minimization,
ICCV09(1436-1443).
IEEE DOI
PDF File. 0909

See also Illumination Recovery From Image With Cast Shadows Via Sparse Representation. BibRef

Fan, H.[Heng], Ling, H.B.[Hai-Bin],
Parallel Tracking and Verifying: A Framework for Real-Time and High Accuracy Visual Tracking,
ICCV17(5487-5495)
IEEE DOI 1802
BibRef
And:
SANet: Structure-Aware Network for Visual Tracking,
DeepLearn-T17(2217-2224)
IEEE DOI 1709
SLAM (robots), learning (artificial intelligence), multi-threading, object tracking, parallel processing, Visualization. Computational modeling, Feature extraction, Recurrent neural networks, Robustness, Target tracking. BibRef

Li, H.X.[Han-Xi], Li, Y.[Yi], Porikli, F.M.[Fatih M.],
DeepTrack: Learning Discriminative Feature Representations Online for Robust Visual Tracking,
IP(25), No. 4, April 2016, pp. 1834-1848.
IEEE DOI 1604
BibRef
Earlier:
DeepTrack: Learning Discriminative Feature Representations by Convolutional Neural Networks for Visual Tracking,
BMVC14(xx-yy).
HTML Version. 1410
BibRef

Li, H.X.[Han-Xi], Li, Y.[Yi], Porikli, F.M.[Fatih M.],
Convolutional neural net bagging for online visual tracking,
CVIU(153), No. 1, 2016, pp. 120-129.
Elsevier DOI 1612
Visual tracking BibRef
Earlier:
Robust Online Visual Tracking with a Single Convolutional Neural Network,
ACCV14(V: 194-209).
Springer DOI 1504
Feature extraction BibRef

Hu, H., Ma, B., Shen, J., Sun, H., Shao, L., Porikli, F.M.[Fatih M.],
Robust Object Tracking Using Manifold Regularized Convolutional Neural Networks,
MultMed(21), No. 2, February 2019, pp. 510-521.
IEEE DOI 1902
Visualization, Manifolds, Target tracking, Laplace equations, Training, Feature extraction, Convolutional neural networks, online tracking BibRef

Zhu, H.[Hao], Porikli, F.M.[Fatih M.],
Automatic Refinement Strategies for Manual Initialization of Object Trackers,
IP(26), No. 2, February 2017, pp. 821-835.
IEEE DOI 1702
computer vision BibRef

Zhu, G.[Gao], Porikli, F.M.[Fatih M.], Li, H.D.[Hong-Dong],
Not All Negatives Are Equal: Learning to Track With Multiple Background Clusters,
CirSysVideo(28), No. 2, February 2018, pp. 314-326.
IEEE DOI 1802
BibRef
Earlier:
Model-Free Multiple Object Tracking with Shared Proposals,
ACCV16(II: 288-304).
Springer DOI 1704
BibRef
And:
Beyond Local Search: Tracking Objects Everywhere with Instance-Specific Proposals,
CVPR16(943-951)
IEEE DOI 1612
BibRef
And:
Robust Visual Tracking with Deep Convolutional Neural Network Based Object Proposals on PETS,
PETS16(1265-1272)
IEEE DOI 1612
Context, Object tracking, Support vector machines, Training, Visualization, Contextual clustering, fine-grained model, tracking by detection BibRef

Hussein, M.[Mohamed], Porikli, F.M.[Fatih M.], Li, R.[Rui], Arslan, S.[Suayb],
CrossTrack: Robust 3D tracking from two cross-sectional views,
CVPR11(1041-1048).
IEEE DOI 1106
BibRef

Ma, B., Huang, L., Shen, J., Shao, L., Yang, M.H., Porikli, F.M.,
Visual Tracking Under Motion Blur,
IP(25), No. 12, December 2016, pp. 5867-5876.
IEEE DOI 1612
image motion analysis BibRef

Huang, L., Ma, B., Shen, J., He, H., Shao, L., Porikli, F.M.[Fatih M.],
Visual Tracking by Sampling in Part Space,
IP(26), No. 12, December 2017, pp. 5800-5810.
IEEE DOI 1710
image sampling, object tracking, probability sampling, Part space, BibRef

Ma, B., Hu, H., Shen, J., Zhang, Y., Porikli, F.M.[Fatih M.],
Linearization to Nonlinear Learning for Visual Tracking,
ICCV15(4400-4407)
IEEE DOI 1602
Dictionaries BibRef

Guo, J., Xu, T.,
Deep Ensemble Tracking,
SPLetters(24), No. 10, October 2017, pp. 1562-1566.
IEEE DOI 1710
convolution, feature extraction, feedforward neural nets, distance metric, template matching problem. BibRef

Cao, Y.[Yi], Ji, H.B.[Hong-Bing], Zhang, W.[Wenbo], Xue, F.[Fei],
Learning spatio-temporal context via hierarchical features for visual tracking,
SP:IC(66), 2018, pp. 50-65.
Elsevier DOI 1806
Visual tracking, Convolutional neural network, Transfer learning, Spatio-temporal context, Training confidence index BibRef

Zhu, Z.G.[Zhi-Gang], Ji, H.B.[Hong-Bing], Zhang, W.[Wenbo], Huang, G.P.[Guo-Peng],
Temporal stochastic linear encoding networks,
SP:IC(70), 2019, pp. 14-20.
Elsevier DOI 1812
Convolutional neural network, Action recognition, Long-range temporal dynamics, Motion boundary BibRef

Hu, X.P.[Xiao-Peng], Li, J.T.[Jing-Ting], Yang, Y.[Yan], Wang, F.[Fan],
Reliability verification-based convolutional neural networks for object tracking,
IET-IPR(13), No. 1, January 2019, pp. 175-185.
DOI Link 1812
BibRef

Wang, T.[Tao], Ling, H.B.[Hai-Bin],
Gracker: A Graph-Based Planar Object Tracker,
PAMI(40), No. 6, June 2018, pp. 1494-1501.
IEEE DOI 1805
Algorithm design and analysis, Benchmark testing, Object tracking, Robustness, Target tracking, Visualization, pose estimation BibRef

Li, Y.D.[Yun-Dong], Zhang, X.[Xueyan], Li, H.G.[Hong-Guang], Zhou, Q.C.[Qi-Chen], Cao, X.B.[Xian-Bin], Xiao, Z.F.[Zhi-Feng],
Object detection and tracking under Complex environment using deep learning-based LPM,
IET-CV(13), No. 2, March 2019, pp. 157-164.
DOI Link 1902
BibRef

Tang, F.H.[Fu-Hui], Lu, X.K.[Xian-Kai], Zhang, X.Y.[Xiao-Yu], Luo, L.K.[Ling-Kun], Hu, S.Q.[Shi-Qiang], Zhang, H.L.[Huan-Long],
Adaptive convolutional layer selection based on historical retrospect for visual tracking,
IET-CV(13), No. 3, April 2019, pp. 345-353.
DOI Link 1904
BibRef

Li, N.[Ning], Ji, Q.G.[Qing-Ge], Ma, T.J.[Tian-Jun],
ACT: an ACTNet for visual tracking,
IET-IPR(13), No. 5, 18 April 2019, pp. 722-728.
DOI Link 1904
BibRef

Zhao, F., Wang, J., Wu, Y., Tang, M.,
Adversarial Deep Tracking,
CirSysVideo(29), No. 7, July 2019, pp. 1998-2011.
IEEE DOI 1907
Target tracking, Visualization, Task analysis, Training, Computational modeling, Neural networks, Correlation, attention BibRef

Teng, Z.[Zhu], Xing, J.L.[Jun-Liang], Wang, Q.[Qiang], Zhang, B.P.[Bao-Peng], Fan, J.P.[Jian-Ping],
Deep Spatial and Temporal Network for Robust Visual Object Tracking,
IP(29), No. 1, 2020, pp. 1762-1775.
IEEE DOI 1912
Target tracking, Visualization, Biological system modeling, Correlation, Training, Benchmark testing, Visual tracking, spatial-temporal LSTM BibRef

Teng, Z.[Zhu], Xing, J.L.[Jun-Liang], Wang, Q.[Qiang], Lang, C.Y.[Cong-Yan], Feng, S.H.[Song-He], Jin, Y.[Yi],
Robust Object Tracking Based on Temporal and Spatial Deep Networks,
ICCV17(1153-1162)
IEEE DOI 1802
feature extraction, learning (artificial intelligence), neural nets, object detection, object tracking, Feature Net, Visualization BibRef

Ge, S., Luo, Z., Zhang, C., Hua, Y., Tao, D.,
Distilling Channels for Efficient Deep Tracking,
IP(29), 2020, pp. 2610-2621.
IEEE DOI 2001
Image coding, Visualization, Correlation, Feature extraction, Adaptation models, Benchmark testing, Minimization, CNNs BibRef

Xu, M.X.[Meng-Xi], Lv, L.[Li], Luan, H.[Hui], Huang, C.R.[Chen-Rong], Fan, T.H.[Tang-Huai],
Object tracking based on learning collaborative representation with adaptive weight,
SIViP(14), No. 2, March 2020, pp. 267-275.
Springer DOI 2003
BibRef

Chen, R.[Rui], Tong, Y.[Ying], Liang, R.[Ruiyu],
Real-Time Generic Object Tracking via Recurrent Regression Network,
IEICE(E103-D), No. 3, March 2020, pp. 602-611.
WWW Link. 2003
BibRef

Huang, K.N.[Kai-Ning], Shi, Y.[Yan], Zhao, F.Q.[Fu-Qi], Zhang, Z.J.[Zi-Jun], Tu, S.S.[Shan-Shan],
Multiple instance deep learning for weakly-supervised visual object tracking,
SP:IC(84), 2020, pp. 115807.
Elsevier DOI 2004
Multiple instance learning (MIL), Weakly-supervised, Object tracking, Multi-view feature learning, Gaussian mixture model BibRef

Tian, S.J.[Sheng-Jing], Shen, S.W.[Shu-Wei], Tian, G.Q.[Guo-Qiang], Liu, X.P.[Xiu-Ping], Yin, B.C.[Bao-Cai],
End-to-end deep metric network for visual tracking,
VC(36), No. 6, June 2020, pp. 1219-1232.
WWW Link. 2005
BibRef

Zhang, Y.[Yang], Tian, X.L.[Xiao-Lin], Jia, N.[Nan], Wang, F.G.[Feng-Ge], Jiao, L.C.[Li-Cheng],
Deep tracking using double-correlation filters by membership weighted decision,
PRL(136), 2020, pp. 161-167.
Elsevier DOI 2008
Visual object tracking, Double-Correlation filter, Membership decision BibRef

Liu, C., Liu, P., Zhao, W., Tang, X.,
Visual Tracking by Structurally Optimizing Pre-Trained CNN,
CirSysVideo(30), No. 9, September 2020, pp. 3153-3166.
IEEE DOI 2009
Target tracking, Visualization, Feature extraction, Task analysis, Image reconstruction, Convolutional codes, Deep learning, one-shot learning BibRef

Li, C.Y.[Chun-Yu], Li, G.[Gang],
Learning multiple instance deep representation for objects tracking,
JVCIR(71), 2020, pp. 102737.
Elsevier DOI 2009
Object tracking, Convolutional networks, Multiple Instance Learning BibRef

Han, Y.M.[Ya-Min], Zhang, P.[Peng], Zhuo, T.[Tao], Huang, W.[Wei], Zha, Y.F.[Yu-Fei], Zhang, Y.N.[Yan-Ning],
Ensemble Tracking Based on Diverse Collaborative Framework With Multi-Cue Dynamic Fusion,
MultMed(22), No. 10, October 2020, pp. 2698-2710.
IEEE DOI 2009
Target tracking, Correlation, Robustness, Adaptation models, Training, Tracking loops, Collaboration, Ensembling structure, heuristic frequency BibRef

Xu, Q.[Qi], Wang, H.B.[Hua-Bin], Wu, Q.[Qilin], Tao, L.[Liang],
Robust online tracking via sparse gradient convolution networks,
SP:IC(90), 2021, pp. 116056.
Elsevier DOI 2012
Online tracking, Convolutional networks, Gradient features, Sparse representation BibRef

Pu, S., Song, Y., Ma, C., Zhang, H., Yang, M.H.,
Learning Recurrent Memory Activation Networks for Visual Tracking,
IP(30), 2021, pp. 725-738.
IEEE DOI 2012
Target tracking, Visualization, Coherence, Generators, Training, Correlation, Recurrent neural networks, Visual tracking, representation BibRef

Xiang, J., Xu, G., Ma, C., Hou, J.,
End-to-End Learning Deep CRF Models for Multi-Object Tracking Deep CRF Models,
CirSysVideo(31), No. 1, January 2021, pp. 275-288.
IEEE DOI 2101
BibRef
And: Erratum: CirSysVideo(31), No. 2, February 2021, pp. 828-828.
IEEE DOI 2102
Target tracking, Machine learning, Recurrent neural networks, Optimization, Task analysis, Standards, Inference algorithms, data association BibRef

Yao, S., Zhang, H., Ren, W., Ma, C., Han, X., Cao, X.,
Robust Online Tracking via Contrastive Spatio-Temporal Aware Network,
IP(30), 2021, pp. 1989-2002.
IEEE DOI 2101
Target tracking, Proposals, Visualization, Task analysis, Detectors, Object tracking, Spatial-temporal modeling, proposal refinement, contrastive online hard example mining BibRef

Zhao, H.J.[Hao-Jie], Yang, G.[Gang], Wang, D.[Dong], Lu, H.C.[Hu-Chuan],
Deep mutual learning for visual object tracking,
PR(112), 2021, pp. 107796.
Elsevier DOI 2102
Visual object tracking, Deep learning, Mutual learning BibRef

Lu, A.D.[An-Dong], Li, C.L.[Cheng-Long], Yan, Y.Q.[Yu-Qing], Tang, J.[Jin], Luo, B.[Bin],
RGBT Tracking via Multi-Adapter Network with Hierarchical Divergence Loss,
IP(30), 2021, pp. 5613-5625.
IEEE DOI 2106
Feature extraction, Target tracking, Data mining, Mobile computing, Adaptation models, Ad hoc networks, Kernel, RGBT tracking, representation learning BibRef

Gurkan, F.[Filiz], Cerkezi, L.[Llukman], Cirakman, O.[Ozgun], Gunsel, B.[Bilge],
TDIOT: Target-Driven Inference for Deep Video Object Tracking,
IP(30), 2021, pp. 7938-7951.
IEEE DOI 2109
Target tracking, Detectors, Proposals, Training, Object tracking, Object detection, Measurement, Deep object detector, region proposal network BibRef

Fan, N.[Nana], Li, X.[Xin], Zhou, Z.[Zikun], Liu, Q.[Qiao], He, Z.Y.[Zhen-Yu],
Noise-Suppressing Deep Tracking,
CirSysVideo(32), No. 4, April 2022, pp. 2238-2250.
IEEE DOI 2204
Target tracking, Kernel, Feature extraction, Visualization, Training, Interference, Task analysis, Visual tracking, polynomial kernel, noise-suppressing representation BibRef

Zhou, Z.[Zikun], Li, X.[Xin], Zhang, T.Z.[Tian-Zhu], Wang, H.P.[Hong-Peng], He, Z.Y.[Zhen-Yu],
Object Tracking via Spatial-Temporal Memory Network,
CirSysVideo(32), No. 5, May 2022, pp. 2976-2989.
IEEE DOI 2205
Target tracking, Context modeling, Adaptation models, Computational modeling, Training, Object tracking, Testing, temporal context BibRef

Cui, Z.Y.[Zhi-Yan], Lu, N.[Na], Wang, W.F.[Wei-Feng],
Pseudo loss active learning for deep visual tracking,
PR(130), 2022, pp. 108773.
Elsevier DOI 2206
Active learning, Visual tracking, Pseudo loss, Pseudo label BibRef

Wang, Y.[Yong], Wei, X.[Xian], Tang, X.[Xuan], Shen, H.[Hao], Zhang, H.L.[Huan-Long],
Adaptive Fusion CNN Features for RGBT Object Tracking,
ITS(23), No. 7, July 2022, pp. 7831-7840.
IEEE DOI 2207
Target tracking, Correlation, Thermal sensors, Radar tracking, Feature extraction, Sensors, Reliability, RGBT tracking, convolutional neural network BibRef

Shahbazi, M.[Mohammad], Bayat, M.H.[Mohammad Hosein], Tarvirdizadeh, B.[Bahram],
A motion model based on recurrent neural networks for visual object tracking,
IVC(126), 2022, pp. 104533.
Elsevier DOI 2209
Single-object tracking, Motion model, Long short-term memory, Recurrent neural network BibRef

Zhang, H.L.[Huan-Long], Cheng, L.Y.[Li-Yun], Zhang, T.Z.[Tian-Zhu], Wang, Y.F.[Yan-Feng], Zhang, W.J., Zhang, J.[Jie],
Target-Distractor Aware Deep Tracking With Discriminative Enhancement Learning Loss,
CirSysVideo(32), No. 9, September 2022, pp. 6267-6278.
IEEE DOI 2209
Target tracking, Feature extraction, Visualization, Sensitivity, Industries, Training, Benchmark testing, Target-distractor aware, visual tracking BibRef

Abdelpakey, M.H.[Mohamed H.], Shehata, M.S.[Mohamed S.],
NullSpaceRDAR: Regularized discriminative adaptive nullspace for object tracking,
IVC(127), 2022, pp. 104550.
Elsevier DOI 2211
Visual object tracking, Joint-nullspace, Convolutional neural network BibRef

Zha, Y.F.[Yu-Fei], Sun, J.X.[Jing-Xian], Zhang, P.[Peng], Zhang, L.C.[Li-Chao], Gonzalez-Garcia, A.[Abel], Huang, W.[Wei],
Self-Supervised Cross-Modal Distillation for Thermal Infrared Tracking,
MultMedMag(29), No. 4, October 2022, pp. 80-96.
IEEE DOI 2301
Target tracking, Training data, Semantics, Training data, Convolutional neural networks, Feature extraction, Annotations, Self-Supervised BibRef

Peng, J.C.[Jing-Chao], Zhao, H.T.[Hai-Tao], Hu, Z.W.[Zheng-Wei],
Dynamic Fusion Network for RGBT Tracking,
ITS(24), No. 4, April 2023, pp. 3822-3832.
IEEE DOI 2304
Convolution, Feature extraction, Kernel, Task analysis, Intelligent transportation systems, Fuses, Reliability, intelligent perception BibRef

Ma, D.[Ding], Wu, X.Q.[Xiang-Qian],
Capsule-Based Regression Tracking via Background Inpainting,
IP(32), 2023, pp. 2867-2878.
IEEE DOI 2306
Target tracking, Routing, Tracking, Feature extraction, Visualization, Task analysis, Semantics, Visual object tracking, capsule networks BibRef

Li, Z.F.[Zhuan-Feng], Xiong, F.C.[Feng-Chao], Zhou, J.[Jun], Lu, J.F.[Jian-Feng], Qian, Y.T.[Yun-Tao],
Learning a Deep Ensemble Network With Band Importance for Hyperspectral Object Tracking,
IP(32), 2023, pp. 2901-2914.
IEEE DOI 2306
Hyperspectral imaging, Target tracking, Object tracking, Visualization, Feature extraction, Task analysis, Videos, ensemble learning BibRef

Wei, H.R.[Hao-Ran], Wan, G.[Gang], Ji, S.P.[Shun-Ping],
ParallelTracker: A Transformer Based Object Tracker for UAV Videos,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Wu, S.[Shan], Hadachi, A.[Amnir], Lu, C.R.[Chao-Ru], Vivet, D.[Damien],
Transformer for multiple object tracking: Exploring locality to vision,
PRL(170), 2023, pp. 70-76.
Elsevier DOI 2306
Multi-object tracking, Transformer, Deep learning, Locality to vision BibRef

Wang, J.[Jian], Tang, X.Y.[Xin-Yi], Hao, Y.F.[Yi-Fan], Wu, D.J.[Dong-Jie], Ye, X.Z.[Xiang-Zhou], Li, Z.[Zheng],
A novel head network and group normalisation help track more accurately,
IET-IPR(17), No. 8, 2023, pp. 2537-2546.
DOI Link 2306
image processing, neural net architecture, object tracking BibRef

Rasol, J.[Jarhinbek], Xu, Y.L.[Yue-Lei], Zhang, Z.X.[Zhao-Xiang], Tao, C.Y.[Cheng-Yang], Hui, T.[Tian],
Bilateral Adversarial Patch Generating Network for the Object Tracking Algorithm,
RS(15), No. 14, 2023, pp. 3670.
DOI Link 2307
BibRef

Dai, K.[Kenan], Zhao, J.[Jie], Wang, L.J.[Li-Jun], Wang, D.[Dong], Li, J.H.[Jian-Hua], Lu, H.C.[Hu-Chuan], Qian, X.S.[Xue-Sheng], Yang, X.Y.[Xiao-Yun],
Video Annotation for Visual Tracking via Selection and Refinement,
ICCV21(10276-10285)
IEEE DOI 2203
Tracking annotations for learning. Geometry, Visualization, Target tracking, Annotations, Video sequences, Image annotation, Training data, BibRef

Li, Z.[Zhuang], Cao, L.L.[Lei-Lei], Wang, H.B.[Hong-Bin],
Limited Sampling Reference Frame for MaskTrack R-CNN,
OVIS21(3847-3850)
IEEE DOI 2112
Training, Image segmentation, Stochastic processes, Object detection, Transformers BibRef

Wu, Q.Q.[Qiang-Qiang], Wan, J.[Jia], Chan, A.B.[Antoni B.],
Progressive Unsupervised Learning for Visual Object Tracking,
CVPR21(2992-3001)
IEEE DOI 2111
Training, Visualization, Real-time systems, Data models, Noise robustness, Pattern recognition, Noise measurement BibRef

Fan, H.[Heng], Ling, H.B.[Hai-Bin],
MART: Motion-Aware Recurrent Neural Network for Robust Visual Tracking,
WACV21(566-575)
IEEE DOI 2106
Location awareness, Visualization, Target tracking, Recurrent neural networks, Dynamics, Estimation, Benchmark testing BibRef

Gozen, D.[Derya], Ozer, S.[Sedat],
Visual Object Tracking in Drone Images with Deep Reinforcement Learning,
ICPR21(10082-10089)
IEEE DOI 2105
Visualization, Target tracking, Reinforcement learning, Cameras, Video surveillance, Complexity theory, Object tracking, UAV videos BibRef

Qian, Y.L.[Yan-Lin], Yan, S.[Song], Lukežic, A.[Alan], Kristan, M.[Matej], Kämäräinen, J.K.[Joni-Kristian], Matas, J.G.[Jirí G.],
DAL: A Deep Depth-Aware Long-term Tracker,
ICPR21(7825-7832)
IEEE DOI 2105
Target tracking, Correlation, Benchmark testing, Information filters, Optimization BibRef

xs Zita, A.[Aleš], Šroubek, F.[Filip],
Tracking Fast Moving Objects by Segmentation Network,
ICPR21(10312-10319)
IEEE DOI 2105
Training, Video sequences, Pipelines, Streaming media, Real-time systems, Generators BibRef

Fang, Y.[Yang], Jo, G.S.[Geun-Sik], Lee, C.H.[Chang-Hee],
RSINet: Rotation-Scale Invariant Network for Online Visual Tracking,
ICPR21(4153-4160)
IEEE DOI 2105
Learning systems, Adaptation models, Visualization, Target tracking, Benchmark testing, Stability analysis, Robustness, real-time tracking BibRef

Zhang, N.[Ning], Liu, J.G.[Jin-Gen], Wang, K.[Ke], Zeng, D.[Dan], Mei, T.[Tao],
Robust Visual Object Tracking with Two-Stream Residual Convolutional Networks,
ICPR21(4123-4130)
IEEE DOI 2105
Deep learning, Training, Visualization, Target tracking, Tracking, Training data, Benchmark testing BibRef

Lee, H.[Hyemin], Kim, I.[Inhan], Kim, D.J.[Dai-Jin],
VAN: Versatile Affinity Network for End-to-end Online Multi-object Tracking,
ACCV20(II:576-593).
Springer DOI 2103
BibRef

Marvasti-Zadeh, S.M.[Seyed Mojtaba], Khaghani, J.[Javad], Ghanei-Yakhdan, H.[Hossein], Kasaei, S.[Shohreh], Cheng, L.[Li],
Comet: Context-aware Iou-guided Network for Small Object Tracking,
ACCV20(II:594-611).
Springer DOI 2103
BibRef

Meshgi, K.[Kourosh], Mirzaei, M.S.[Maryam Sadat], Oba, S.[Shigeyuki],
Leveraging Tacit Information Embedded in CNN Layers for Visual Tracking,
ACCV20(II:521-538).
Springer DOI 2103
BibRef

Feng, J., Zhao, K., Song, X., Li, A., Zhang, H.,
Robust Visual Tracking Via An Imbalance-Elimination Mechanism,
VCIP20(531-534)
IEEE DOI 2102
learning (artificial intelligence), object tracking, pattern classification, random processes, sampling methods, negative patterns BibRef

Liao, B.Y.[Bing-Yan], Wang, C.Y.[Chen-Ye], Wang, Y.[Yayun], Wang, Y.N.[Yao-Nong], Yin, J.[Jun],
PG-Net: Pixel to Global Matching Network for Visual Tracking,
ECCV20(XXII:429-444).
Springer DOI 2011
BibRef

Zhang, R., Fan, C., Ming, Y., Fu, H., Meng, X.,
An Effective Hierarchical Resolution Learning Method for Low-Resolution Targets Tracking,
ICIP20(2076-2080)
IEEE DOI 2011
Target tracking, Spatial resolution, Shape, Visualization, Image reconstruction, Image edge detection, Visual tracking, Super-resolution reconstruction BibRef

Guo, Q.[Qing], Cheng, Z.Y.[Zi-Yi], Xu, F.J.F.[Felix Jue-Fei], Ma, L.[Lei], Xie, X.F.[Xiao-Fei], Liu, Y.[Yang], Zhao, J.J.[Jian-Jun],
Learning to Adversarially Blur Visual Object Tracking,
ICCV21(10819-10828)
IEEE DOI 2203
Training, Visualization, Costs, Codes, Linear programming, Cameras, Motion and tracking, Adversarial learning BibRef

Guo, Q.[Qing], Xie, X.F.[Xiao-Fei], Juefei-Xu, F.[Felix], Ma, L.[Lei], Li, Z.G.[Zhong-Guo], Xue, W.L.[Wan-Li], Feng, W.[Wei], Liu, Y.[Yang],
Spark: Spatial-aware Online Incremental Attack Against Visual Tracking,
ECCV20(XXV:202-219).
Springer DOI 2011
BibRef

Liang, S.Y.[Si-Yuan], Wei, X.X.[Xing-Xing], Yao, S.Y.[Si-Yuan], Cao, X.C.[Xiao-Chun],
Efficient Adversarial Attacks for Visual Object Tracking,
ECCV20(XXVI:34-50).
Springer DOI 2011
BibRef

Rout, L.[Litu], Raju, P.M.[Priya Mariam], Mishra, D.[Deepak], Subrahmanyam, G.R.K.S.[Gorthi Rama Krishna Sai],
Learning Rotation Adaptive Correlation Filters in Robust Visual Object Tracking,
ACCV18(II:646-661).
Springer DOI 1906
BibRef

Rout, L.[Litu], Siddhartha, Mishra, D.[Deepak], Subrahmanyam, G.R.K.S.[Gorthi Rama Krishna Sai],
Rotation Adaptive Visual Object Tracking with Motion Consistency,
WACV18(1047-1055)
IEEE DOI 1806
convolution, feature selection, feedforward neural nets, image capture, image motion analysis, image sequences, Visualization BibRef

Wang, L.[Li], Pham, N.T.[Nam Trung], Ng, T.T.[Tian-Tsong], Wang, G.[Gang], Chan, K.L.[Kap Luk], Leman, K.[Karianto],
Learning Deep Features for Multiple Object Tracking by Using a Multi-Task Learning Strategy,
ICIP14(838-842)
IEEE DOI 1502
Adaptation models BibRef

Wang, N.[Ning], Song, Y.B.[Yi-Bing], Ma, C.[Chao], Zhou, W.G.[Wen-Gang], Liu, W.[Wei], Li, H.Q.A.[Hou-Qi-Ang],
Unsupervised Deep Tracking,
CVPR19(1308-1317).
IEEE DOI 2002
BibRef

Li, X.[Xin], Ma, C.[Chao], Wu, B.Y.[Bao-Yuan], He, Z.Y.[Zhen-Yu], Yang, M.H.[Ming-Hsuan],
Target-Aware Deep Tracking,
CVPR19(1369-1378).
IEEE DOI 2002
BibRef

Che, M.Q.[Man-Qiang], Wang, R.L.[Run-Ling], Lu, Y.[Yan], Li, Y.[Yan], Zhi, H.[Hui], Xiong, C.Z.[Chang-Zhen],
Channel Pruning for Visual Tracking,
VOT18(I:70-82).
Springer DOI 1905
BibRef

Zhai, M.Y.[Meng-Yao], Chen, L.[Lei], Mori, G.[Greg], Roshtkhari, M.J.[Mehrsan Javan],
Deep Learning of Appearance Models for Online Object Tracking,
WiCV-E18(IV:681-686).
Springer DOI 1905
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Jung, I.[Ilchae], Son, J.[Jeany], Baek, M.[Mooyeol], Han, B.H.[Bo-Hyung],
Real-Time MDNet,
ECCV18(II: 89-104).
Springer DOI 1810
multi-domain convolutional neural network for tracking. BibRef

Zhou, H.Z.[Hui-Zhong], Ummenhofer, B.[Benjamin], Brox, T.[Thomas],
DeepTAM: Deep Tracking and Mapping,
ECCV18(XVI: 851-868).
Springer DOI 1810
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Kokul, T., Fookes, C., Sridharan, S., Ramanan, A., Pinidiyaarachchi, U.A.J.,
Gate connected convolutional neural network for object tracking,
ICIP17(2602-2606)
IEEE DOI 1803
Adaptation models, Logic gates, Machine learning, Network architecture, Object tracking, Target tracking, object tracking BibRef

Chakrabory, A.[Anit], Dutta, S.[Sayandip],
A Machine Learning Inspired Approach for Detection, Recognition and Tracking of Moving Objects from Real-Time Video,
PReMI17(170-178).
Springer DOI 1711
BibRef

Song, Y., Ma, C., Gong, L., Zhang, J., Lau, R.W.H., Yang, M.H.,
CREST: Convolutional Residual Learning for Visual Tracking,
ICCV17(2574-2583)
IEEE DOI 1802
convolution, feature extraction, learning (artificial intelligence), neural nets, object tracking, Visualization BibRef

Serratosa, F.[Francesc], Amézquita Gómez, N.[Nicolás], Alquézar, R.[René],
Combining Neural Networks and Clustering Techniques for Object Recognition in Indoor Video Sequences,
CIARP06(399-405).
Springer DOI 0611
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Siamese Networks for Tracking .