Relative Depth-Guided Cross-Domain Semantic Segmentation for High-Resolution Satellite Remote Sensing Images (opens in new tab)

Satellite remote sensing images exhibit significant cross-domain discrepancies due to variations in sensors, imaging conditions, and regional characteristics. These discrepancies degrade the performance of semantic segmentation models on unseen target domains. Unsupervised domain adaptation (UDA) mitigates this problem but requires target-domain images during training. Achieving robust cross-domain generalization (DG) with foundation models typically relies on large-scale architectures, incur...