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Salient object detection aims to identify the most attractive objects from images. However, their boundaries are typically of poor quality when predicted using available methods. One or multiple objects may also be left undetected if the image contains multiple objects. To solve these problems, this article proposes the novel cross refinement network, which consists of a Res2Net-based backbone network; a fusion network equipped with four convolutional block attention modules and fourdoi:10.1049/sil2.12041 fatcat:eljmpaxoujeqhcmlntn2id5cae