HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation

Benchmark Model Rank Results
domain-adaptation-on-cityscapes-to-acdcHRDA#7mIoU: 68.0
domain-adaptation-on-gta5-to-cityscapesHRDA#6mIoU: 73.8
domain-adaptation-on-synthia-to-cityscapesHRDA#7mIoU: 65.8
image-to-image-translation-on-gtav-toHRDA#3mIoU: 73.8
image-to-image-translation-on-synthia-toHRDA#3mIoU (13 classes): 72.4
semantic-segmentation-on-dark-zurichHRDA#5mIoU: 55.9
semantic-segmentation-on-gtav-to-cityscapes-1HRDA#3mIoU: 73.8
semantic-segmentation-on-synthia-toHRDA#3Mean IoU: 65.8
synthetic-to-real-translation-on-gtav-toHRDA#5mIoU: 73.8
synthetic-to-real-translation-on-synthia-to-1HRDA#5MIoU (16 classes): 65.8MIoU (13 classes): 72.4
unsupervised-domain-adaptation-on-gtav-toHRDA#4mIoU: 73.8
unsupervised-domain-adaptation-on-synthia-toHRDA#5mIoU (13 classes): 72.4mIoU: 65.8