RSPoint-SAM: A SAM-Driven Method With Cross-Level Feature Fusion for Point Supervised Segmentation (opens in new tab)

Deep learning (DL) has made significant progress in the semantic segmentation of remote sensing (RS) images. However, its great performance heavily depends on high-quality annotations, which greatly restrict further advancement. Recently, the segment anything model (SAM), enabled by large-scale pretraining and flexible prompt mechanisms, has shown exceptional zero-shot segmentation ability for any object. Hence, we devise RSPoint-SAM, a SAM-based point-supervised semantic segmentation model t...