Prompting DirectSAM for Semantic Contour Extraction in Remote Sensing Images

Understand

The Direct Segment Anything Model (DirectSAM) excels in class-agnostic contour extraction.

• In this paper, we explore its use by applying it to optical remote sensing imagery, where semantic contour extraction-such as identifying buildings, road networks, and coastlines-holds significant practical value.
• Those applications are currently handled via training specialized small models separately on small datasets in each domain.
• We introduce a foundation model derived from DirectSAM, termed DirectSAM-RS, which not only inherits the strong segmentation capability acquired from natural images, but also benefits from a large-scale dataset we created for remote sensing semantic contour extraction.