FoR-Net: Learning to Focus on Hard Regions for Efficient Semantic Segmentation 事件

FoR-Net: Learning to Focus on Hard Regions for Efficient Semantic Segmentation arXiv:2605.02764v2 Announce Type: replace Abstract: We present FoR-Net, an efficient semantic segmentation framework that focuses on identifying and enhancing hard regions. Instead of relying on heavy global modeling, FoR-Net adopts an efficient strategy that selectively emphasizes informative regions through a learned importance map and a Top-K activation mechanism. Specifically, a selector module predicts region-wi