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SotA/Medical/Semantic Segmentation/Cityscapes test

Semantic Segmentation on Cityscapes test

Metric: PQ (higher is better)

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#Model↕PQ▼Extra DataPaperDate↕Code
1OneFormer (ConvNeXt-L, single-scale, Mapillary Vistas-Pretrained)68YesOneFormer: One Transformer to Rule Universal Ima...2022-11-10Code
2Panoptic-DeepLab (SWideRNet [1, 1, 4.5], Mapillary, multi-scale)67.8YesScaling Wide Residual Networks for Panoptic Segm...2020-11-23-
3EfficientPS67.1YesEfficientPS: Efficient Panoptic Segmentation2020-04-05Code
4Axial-DeepLab-XL (Mapillary Vistas, multi-scale)66.6YesAxial-DeepLab: Stand-Alone Axial-Attention for P...2020-03-17Code
5kMaX-DeepLab (single-scale)66.2NokMaX-DeepLab: k-means Mask Transformer2022-07-08Code
6Panoptic-Deeplab65.5YesPanoptic-DeepLab: A Simple, Strong, and Fast Bas...2019-11-22Code
7EfficientPS (Cityscapes-fine)62.9NoEfficientPS: Efficient Panoptic Segmentation2020-04-05Code
8SOGNet (ResNet-50)60NoSOGNet: Scene Overlap Graph Network for Panoptic...2019-11-18Code
9COPS (ResNet-50)60NoCombinatorial Optimization for Panoptic Segmenta...2021-06-06Code
10Dynamically Instantiated Network55.4NoPixelwise Instance Segmentation with a Dynamical...2017-04-07Code