A Domain Adaptive Semantic Segmentation Method Using Contrastive Learning and Data Augmentation
Yixiao Xiang,
Lihua Tian,
Chen Li
Abstract:For semantic segmentation tasks, it is expensive to get pixel-level annotations on real images. Domain adaptation eliminates this process by transferring networks trained on synthetic images to real-world images. As one of the mainstream approaches to domain adaptation, most of the self-training based domain adaptive methods focus on how to select high confidence pseudo-labels, i.e., to obtain domain invariant knowledge indirectly. A more direct means to explicitly align the data of the source and target domai… Show more
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