Semantic Segmentation

Semantic segmentation assigns a class label to every pixel — the dense prediction problem that underpins autonomous driving, medical imaging, and satellite analysis. FCN (2015) showed you could repurpose classifiers for pixel labeling, DeepLab introduced atrous convolutions and CRFs, and SegFormer (2021) proved transformers dominate here too. State-of-the-art on Cityscapes exceeds 85 mIoU, but ADE20K with its 150 classes remains brutally challenging. The frontier has moved toward universal segmentation models like Mask2Former that handle semantic, instance, and panoptic segmentation in a single architecture.