FoR-Net improves efficiency in semantic segmentation by focusing on hard regions with a learned selector and multi-scale convolutions, achieving competitive results on Cityscapes.
Deep dual-resolution networks for real-time and accurate semantic segmentation, in: CVPR
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FoR-Net: Learning to Focus on Hard Regions for Efficient Semantic Segmentation
FoR-Net improves efficiency in semantic segmentation by focusing on hard regions with a learned selector and multi-scale convolutions, achieving competitive results on Cityscapes.