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Long-term tracking requires extreme stability to the multitude of model updates and robustness to the disappearance and loss of the target as such will inevitably happen.
Visual object tracking using adaptive correlation filters
D. S. Bolme, J. R. Beveridge, B. A. Draper, and Y. M. Lui · 2010
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Tracking-learning-detection
Z. Kalal, K. Mikolajczyk, and J. Matas · 2010
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Rectified linear units improve restricted boltzmann machines
V. Nair and G. E. Hinton · 2010
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Struck: Structured output tracking with kernels
S. Hare, A. Saffari, and P. H. Torr · 2011
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Self-paced learning for long-term tracking
J. S. Supancic and D. Ramanan · 2013
Earlier work this paper cites.
Accurate scale estimation for robust visual tracking
M. Danelljan, G. Hager, F. Shahbaz Khan, and M. Felsberg · 2014
Earlier work this paper cites.
Adaptive color attributes for real-time visual tracking
M. Danelljan, F. Shahbaz Khan, M. Felsberg, and J. van de Weijer · 2014
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Object tracking by oversampling local features
F. Pernici and A. D. Bimbo · 2014
Earlier work this paper cites.
Visual tracking: an experimental survey
A. W. M. Smeulders, D. M. Chu, R. Cucchiara, S. Calderara, A. Dehghan, and M. Shah · 2014
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Learning spatially regularized correlation filters for visual tracking
M. Danelljan, G. Häger, F. Khan, and M. Felsberg · 2015
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High-speed tracking with kernelized correlation filters
J. F. Henriques, R. Caseiro, P. Martins, and J. Batista · 2015
Cited alongside, same era.
Multi-store tracker (muster): A cognitive psychology inspired approach to object tracking
Z. Hong, Z. Chen, C. Wang, X. Mei, D. Prokhorov, and D. Tao · 2015
Cited alongside, same era.
Correlation filters with limited boundaries
H. Kiani Galoogahi, T. Sim, and S. Lucey · 2015
Cited alongside, same era.
The visual object tracking vot2015 challenge results
M. Kristan, J. Matas, A. Leonardis, M. Felsberg, L. Cehovin, G. Fernandez, T. Vojir, G. Hager, G. Nebehay, and R. Pflugfelder · 2015
Cited alongside, same era.
Hierarchical convolutional features for visual tracking
C. Ma, J.-B. Huang, X. Yang, and M.-H. Yang · 2015
Cited alongside, same era.
Long-term correlation tracking
C. Ma, X. Yang, C. Zhang, and M.-H. Yang · 2015
Cited alongside, same era.
Beyond correlation filters: learning continuous convolution operators for visual tracking
M. Danelljan, A. Robinson, F. S. Khan, and M. Felsberg · 2016
Later among the works it cites.
A benchmark and simulator for uav tracking
M. Mueller, N. Smith, and B. Ghanem · 2016
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Learning multi-domain convolutional neural networks for visual tracking
H. Nam and B. Han · 2016
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Hedged deep tracking
Y. Qi, S. Zhang, L. Qin, H. Yao, Q. Huang, J. Lim, and M.-H. Yang · 2016
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Siamese instance search for tracking
R. Tao, E. Gavves, and A. W. M. Smeulders · 2016
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Beyond local search: Tracking objects everywhere with instance-specific proposals
G. Zhu, F. Porikli, and H. Li · 2016
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2015
Cited alongside, same era.
Object tracking benchmark
Y. Wu, J. Lim, and M.-H. Yang · 2015
Cited alongside, same era.
Staple: Complementary learners for real-time tracking
L. Bertinetto, J. Valmadre, S. Golodetz, O. Miksik, and P. H. S. Torr · 2016
Cited alongside, same era.
Fully-convolutional siamese networks for object tracking
L. Bertinetto, J. Valmadre, J. F. Henriques, A. Vedaldi, and P. H. Torr · 2016
Cited alongside, same era.
Later among the works it cites.
Visual tracking by reinforced decision making
J. Choi, J. Kwon, and K. M. Lee · 2017
Closest in time.
Eco: Efficient convolution operators for tracking
M. Danelljan, G. Bhat, F. S. Khan, and M. Felsberg · 2017
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Discriminative correlation filter with channel and spatial reliability
A. Lukežič, T. Vojíř, L. Čehovin, J. Matas, and M. Kristan · 2017
Closest in time.
End-to-end representation learning for correlation filter based tracking
J. Valmadre, L. Bertinetto, J. F. Henriques, A. Vedaldi, and P. H. Torr · 2017
Closest in time.