RFNET: Refined Fusion Three-Branch RGB-D Salient Object Detection Network

Abstract

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Salient Object Detection (SOD) aims to identify the most attractive objects in an image. To solve the problem that existing RGB-D SOD methods cannot fully utilize multimodal information to localize objects accurately, we propose a novel Refined Fusion Three-Branch network(RFNet). Firstly, the Comprehensive Attentive Fusion module is designed to encode the fusion of features from different modalities and suppress the background noise. Secondly, the Intermediate Refinement Connection module is designed to remove redundant multimodal information and refine the features. Finally, experiments on public benchmark datasets demonstrate the good performance of our method for both quantitative and qualitative evaluation. The source code is publicly available as https://github.com/Corgislam/RFNet-code