AI RESEARCH
RSONet: Region-guided Selective Optimization Network for RGB-T Salient Object Detection
arXiv CS.CV
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ArXi:2603.12685v1 Announce Type: new This paper focuses on the inconsistency in salient regions between RGB and thermal images. To address this issue, we propose the Region-guided Selective Optimization Network for RGB-T Salient Object Detection, which consists of the region guidance stage and saliency generation stage. In the region guidance stage, three parallel branches with same encoder-decoder structure equipped with the context interaction (CI) module and spatial-aware fusion (SF) module are designed to generate the guidance maps which are leveraged to calculate similarity scores.