2019
Domain Adaptation for Semantic Segmentation With Maximum Squares Loss
ICCV 2019poster
Deep neural networks for semantic segmentation always require a large number of samples with pixel-level labels, which becomes the major difficulty in their real-world applications. To reduce the labeling cost, unsupervised domain adaptation (UDA) approaches are proposed to transfer knowledge from l…