MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation

Benchmark Model Rank Results
domain-adaptation-on-cityscapes-to-acdcMIC#6mIoU: 70.4
domain-adaptation-on-gta5-to-cityscapesMIC#4mIoU: 75.9
domain-adaptation-on-office-homeMIC#5Accuracy: 86.2
domain-adaptation-on-synthia-to-cityscapesMIC#5mIoU: 67.3
domain-adaptation-on-visda2017MIC#3Accuracy: 92.8
image-to-image-translation-on-cityscapes-toMIC#1mAP: 47.6
image-to-image-translation-on-gtav-toMIC#1mIoU: 75.9
image-to-image-translation-on-synthia-toMIC#2mIoU (13 classes): 74.0
semantic-segmentation-on-dark-zurichMIC#3mIoU: 60.2
semantic-segmentation-on-gtav-to-cityscapes-1MIC#1mIoU: 75.9
semantic-segmentation-on-synthia-toMIC#2Mean IoU: 67.3
synthetic-to-real-translation-on-gtav-toHRDA+MIC#2mIoU: 75.9
synthetic-to-real-translation-on-synthia-to-1MIC#3MIoU (16 classes): 67.3MIoU (13 classes): 74.0
unsupervised-domain-adaptation-on-cityscapes-1MIC#4mAP@0.5: 47.6
unsupervised-domain-adaptation-on-gtav-toMIC#1mIoU: 75.9
unsupervised-domain-adaptation-on-synthia-toMIC#4mIoU (13 classes): 74.0mIoU: 67.3