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Found 2 papers, 1 papers with code
Conditional Boundary Loss for Semantic Segmentation
We conduct extensive experiments on ADE20K, Cityscapes, and Pascal Context, and the results show that applying the CBL to various popular segmentation networks can significantly improve the mIoU and boundary F-score performance.
Ranked #22 on
Semantic Segmentation
on Cityscapes val
Semantic Segmentation via Pixel-to-Center Similarity Calculation
Under this novel view, we propose a Class Center Similarity layer (CCS layer) to address the above-mentioned challenges by generating adaptive class centers conditioned on different scenes and supervising the similarities between class centers.
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