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One of the major challenges of model-free visual tracking problem has been the difficulty originating from the unpredictable and drastic changes in the appearance of objects we target to track.
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Online tracking by learning discriminative saliency map with convolutional neural network
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T. Zhang, A. Bibi, and B. Ghanem · 2016
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Once for all: a two-flow convolutional neural network for visual tracking
K. Chen and W. Tao · 2017
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Eco: Efficient convolution operators for tracking
M. Danelljan, G. Bhat, F. Khan, and M. Felsberg · 2017
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Discriminative correlation filter with channel and spatial reliability
A. Lukezic, T. Vojir, L. Cehovin Zajc, J. Matas, and M. Kristan · 2017
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J. Supancic, III and D. Ramanan · 2017
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End-to-end representation learning for correlation filter based tracking
J. Valmadre, L. Bertinetto, J. Henriques, A. Vedaldi, and P. H. S. Torr · 2017
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Action-decision networks for visual tracking with deep reinforcement learning
S. Yun, J. Choi, Y. Yoo, K. Yun, and J. Young Choi · 2017
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