Frequency Decomposition-Driven Unsupervised Domain Adaptation for Remote Sensing Image Semantic Segmentation

arXiv:2404.04531v1 Announce Type: new
Abstract: Cross-domain semantic segmentation of remote sensing (RS) imagery based on unsupervised domain adaptation (UDA) techniques has significantly advanced deep-learning applications in the geosciences. Recently, with its ingenious and versatile architecture, the Transformer model has been successfully applied in RS-UDA tasks. However, existing UDA methods mainly focus on domain alignment in the high-level feature space. It is still challenging to retain cross-domain local spatial details and global contextual semantics simultaneously, which is crucial for the RS …

arxiv cs.cv domain domain adaptation image segmentation semantic sensing type unsupervised