UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery

Benchmark Model Rank Results
semantic-segmentation-on-potsdamUnetFormer#2mIoU: 85.18
semantic-segmentation-on-isprs-potsdamFT-UNetFormer#3Overall Accuracy: 92.0Mean F1: 93.3Mean IoU: 87.5
semantic-segmentation-on-isprs-potsdamUNetFormer#8Overall Accuracy: 91.3Mean F1: 92.8Mean IoU: 86.8
semantic-segmentation-on-isprs-vaihingenFT-UNetFormer#4Overall Accuracy: 91.6Average F1: 91.3Category mIoU: 84.1
semantic-segmentation-on-isprs-vaihingenUNetFormer#5Overall Accuracy: 91.0Average F1: 90.4Category mIoU: 82.7
semantic-segmentation-on-vaihingenUnetFormer#4mIoU: 77.24
semantic-segmentation-on-us3dUNetFormer#5mIoU: 74.77
semantic-segmentation-on-uavidUNetFormer#6Mean IoU: 67.8
semantic-segmentation-on-lovedaUNetFormer#14Category mIoU: 52.40