Li, Dongdong; Wen, Gongjian; Kuai, Yangliu; Xiao, Jingjing; Porikli, Fatih
Discriminative Correlation Filters (DCF) have achieved enormous popularity in the tracking community. Generally, DCF based trackers assume that the target can be well shaped by an axis-aligned bounding box. Therefore, in terms of irregularly shaped objects, the learned correlation filter is unavoidably deteriorated by the background pixels inside the bounding box. To tackle this problem, we propose Target-Aware Correlation Filters (TACF) for visual tracking. A target likelihood map is...[Show more]
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