Abstract
Diffusion-based salient region detection has recently received intense research attention. In this paper, we propose a salient region detection method based on the foreground and background propagation with manifold ranking. By considering the spatial variance of superpixel clusters, foreground and background seed regions are extracted preliminarily. Then, in order to produce a pixel-accurate saliency map covering the salient objects more uniformly, we propagate the foreground and background seed regions through the diffusion process. Experimental results on public benchmark databases show that the proposed method can completely highlight the salient regions and sufficiently suppress the background regions.
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