Jiajie Mai1, Xuemiao Xu2,*, Guorong Xiao3, Zijun Deng2, Jiaxing Chen2
Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 847-855, 2020, DOI:10.32604/iasc.2020.010119
Abstract The Salient object detection aims to segment out the most visually distinctive
objects in an image, which is a challenging task in computer vision. In this
paper, we present the PGCA-Net equipped with the pyramid guided channel
attention fusion block (PGCAFB) for the saliency detection task. Given an input
image, the hierarchical features are extracted using a deep convolutional neural
network (DCNN), then starting from the highest-level semantic features, we
stage-by-stage restore the spatial saliency details by aggregating the lowerlevel detailed features. Since for the weak discriminative ability of the shallow
detailed features, directly introducing them to the semantic features… More >