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Discriminative Scale Space Tracking
Compared to the standard exhaustive scale search, our approach achieves a gain of 2. 5% in average overlap precision on the OTB dataset.
Adaptive Decontamination of the Training Set: A Unified Formulation for Discriminative Visual Tracking
We propose a novel generic approach for alleviating the problem of corrupted training samples in tracking-by-detection frameworks.
Learning Spatially Regularized Correlation Filters for Visual Tracking
These methods utilize a periodic assumption of the training samples to efficiently learn a classifier on all patches in the target neighborhood.
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