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Saliency Detection via A Graph Based Diffusion Model

机译:通过基于图的扩散模型进行显着性检测

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摘要

This paper proposes a graph based diffusion method for image saliency detection problem by adopting random walk with restart (RWR) model. Our method begins with computing background and foreground priors respectively for the input image. Based on these priors, we then adopt RWR method to obtain more reasonable and accurate background and foreground measurements by further considering the local structure of image. At last, we combine both background and foreground measurements together to obtain a more accurate saliency estimation. Experimental evaluations on four benchmark datasets demonstrate the benefits and effectiveness of the proposed method.
机译:本文提出了一种基于图的扩散方法,通过采用随机重启重启(RWR)模型来解决图像显着性检测问题。我们的方法从分别计算输入图像的背景和前景先验开始。基于这些先验,我们通过进一步考虑图像的局部结构,采用RWR方法来获得更合理,更准确的背景和前景测量。最后,我们将背景和前景测量结合在一起以获得更准确的显着性估计。对四个基准数据集的实验评估证明了该方法的好处和有效性。

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