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9500
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Robust Visual Tracking and Vehicle Classification via Sparse
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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
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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.[Fuqi],
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.[Fengge],
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
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.[Jirí],
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.[Ziyi],
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
BibRef
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
BibRef
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 .