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Deep neural networks, albeit their great success on feature learning in various computer vision tasks, are usually considered as impractical for online visual tracking because they require very long training time and a large number of training samples.
“Estimating a kernel fisher discriminant in the presence of label noise,”
Neil D Lawrence and Bernhard Schölkopf, · 2001
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“Color-based probabilistic tracking,”
Patrick Pérez, Carine Hue, Jaco Vermaak, and Michel Gangnet, · 2002
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“Distinctive image features from scale-invariant keypoints,”
David G Lowe, · 2004
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“Online selection of discriminative tracking features,”
Robert T. Collins, Yanxi Liu, and Marius Leordeanu, · 2005
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“Histograms of oriented gradients for human detection,”
Navneet Dalal and Bill Triggs, · 2005
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“Multiple instance boosting for object detection,”
Paul Viola, John Platt, Cha Zhang, et al., · 2005
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“Robust fragments-based tracking using the integral histogram,”
Amit Adam, Ehud Rivlin, and Ilan Shimshoni, · 2006
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“Face description with local binary patterns: Application to face recognition,”
Timo Ahonen, Abdenour Hadid, and Matti Pietikainen, · 2006
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“Incremental learning for robust visual tracking,”
David A. Ross, Jongwoo Lim, Ruei-Sung Lin, and Ming-Hsuan Yang, · 2008
Earlier work this paper cites.
“Visual tracking with online multiple instance learning,”
Boris Babenko, Ming-Hsuan Yang, and Serge Belongie, · 2009
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“Learning convolutional feature hierachies for visual recognition,”
Koray Kavukcuoglu, Pierre Sermanet, Y-Lan Boureau, Karol Gregor, Michaël Mathieu, and Yann LeCun, · 2010
Earlier work this paper cites.
“Human tracking using convolutional neural networks,”
Jialue Fan, Wei Xu, Ying Wu, and Yihong Gong, · 2010
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“Random classification noise defeats all convex potential boosters,”
Philip M Long and Rocco A Servedio, · 2010
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“The pascal visual object classes (voc) challenge,”
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman, · 2010
Cited alongside, same era.
“Pn learning: Bootstrapping binary classifiers by structural constraints,”
Zdenek Kalal, Jiri Matas, and Krystian Mikolajczyk, · 2010
Cited alongside, same era.
“Visual tracking decomposition,”
Junseok Kwon and Kyoung Mu Lee, · 2010
Cited alongside, same era.
“Struck: Structured output tracking with kernels,”
Sam Hare, Amir Saffari, and Philip HS Torr, · 2011
Cited alongside, same era.
“Visual tracking with online multiple instance learning,”
Boris Babenko, Ming-Hsuan Yang, and Serge Belongie, · 2011
Cited alongside, same era.
“Context tracker: Exploring supporters and distracters in unconstrained environments,”
Thang Ba Dinh, Nam Vo, and Gérard Medioni, · 2011
Cited alongside, same era.
“Learning with noisy labels,”
Nagarajan Natarajan, Inderjit S Dhillon, Pradeep K Ravikumar, and Ambuj Tewari, · 2013
Later among the works it cites.
“Robust object tracking with online multi-lifespan dictionary learning,”
Junliang Xing, Jin Gao, Bing Li, Weiming Hu, and Shuicheng Yan, · 2013
Later among the works it cites.
“Online object tracking: A benchmark,”
Yi Wu, Jongwoo Lim, and Ming-Hsuan Yang, · 2013
Later among the works it cites.
“The visual object tracking vot2013 challenge results,”
Matej Kristan, Roman Pflugfelder, Ale Leonardis, Jiri Matas, Fatih Porikli, Luka Cehovin, Georg Nebehay, Gustavo Fernandez, Toma Vojir, Adam Gatt, et al., · 2013
Later among the works it cites.
“Enhanced distribution field tracking using channel representations,”
Michael Felsberg, · 2013
Later among the works it cites.
“An enhanced adaptive coupled-layer lgtracker++,”
Jingjing Xiao, Rustam Stolkin, and Ale Leonardis, · 2013
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“Robustifying the flock of trackers,”
Andreas Wendel, Sabine Sternig, and Martin Godec, · 2011
Cited alongside, same era.
“Imagenet classification with deep convolutional neural networks,”
Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton, · 2012
Cited alongside, same era.
“Multi-column deep neural networks for image classification,”
Dan Claudiu Ciresan, Ueli Meier, and Jürgen Schmidhuber, · 2012
Cited alongside, same era.
“Visual tracking via adaptive structural local sparse appearance model,”
Xu Jia, Huchuan Lu, and Ming-Hsuan Yang, · 2012
Cited alongside, same era.
“Robust object tracking via sparsity-based collaborative model,”
Wei Zhong, Huchuan Lu, and Ming-Hsuan Yang, · 2012
Cited alongside, same era.
“Representation learning: A review and new perspectives,”
Y. Bengio, A. Courville, and P. Vincent, · 2013
Cited alongside, same era.
Later among the works it cites.
“A protocol for evaluating video trackers under real-world conditions,”
Tahir Nawaz and Andrea Cavallaro, · 2013
Later among the works it cites.
“Rich feature hierarchies for accurate object detection and semantic segmentation,”
Ross Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik, · 2014
Later among the works it cites.
“Part-based r-cnns for fine-grained category detection,”
Ning Zhang, Jeff Donahue, Ross Girshick, and Trevor Darrell, · 2014
Later among the works it cites.
“Deeptrack: Learning discriminative feature representations by convolutional neural networks for visual tracking,”
Hanxi Li, Yi Li, and Fatih Porikli, · 2014
Later among the works it cites.
“Robust online visual tracking with an single convolutional neural network,”
Hanxi Li, Yi Li, and Fatih Porikli, · 2014
Later among the works it cites.
“Transfer learning based visual tracking with gaussian processes regression,”
Jin Gao, Haibin Ling, Weiming Hu, and Junliang Xing, · 2014
Later among the works it cites.
“High-speed tracking with kernelized correlation filters,”
J. F. Henriques, R. Caseiro, P. Martins, and J. Batista, · 2015
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