AI RESEARCH
PC-SAM: Patch-Constrained Fine-Grained Interactive Road Segmentation in High-Resolution Remote Sensing Images
arXiv CS.CV
•
ArXi:2604.00495v1 Announce Type: new Road masks obtained from remote sensing images effectively a wide range of downstream tasks. In recent years, most studies have focused on improving the performance of fully automatic segmentation models for this task, achieving significant gains. However, current fully automatic methods are still insufficient for identifying certain challenging road segments and often produce false positive and false negative regions. Moreover, fully automatic segmentation does not local segmentation of regions of interest or refinement of existing masks.