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Face hallucination is a domain-specific super-resolution problem with the goal to generate high-resolution (HR) faces from low-resolution (LR) input images. In contrast to existing methods that often learn a single patch-to-patch mapping from LR to HR images and are regardless of the contextual interdependency between patches, we propose a novel Attention-aware Face Hallucination (Attention-FH) framework...
In this paper we propose a novel kernel-based tracking approach using weighted fragments. We represent the target with multiple fragments and define the weight of each fragment using the proportion of object and background distributions. We invoke an independent mean shift tracker for each fragment and then combine the tracking results of all the fragments in a linear weighting scheme. The proposed...
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