Segment Anything Model for Road Network Graph Extraction

arXiv:2403.16051v1 Announce Type: new
Abstract: We propose SAM-Road, an adaptation of the Segment Anything Model (SAM) for extracting large-scale, vectorized road network graphs from satellite imagery. To predict graph geometry, we formulate it as a dense semantic segmentation task, leveraging the inherent strengths of SAM. The image encoder of SAM is fine-tuned to produce probability masks for roads and intersections, from which the graph vertices are extracted via simple non-maximum suppression. To predict graph topology, we designed a lightweight transformer-based …

arxiv cs.cv extraction graph network segment segment anything segment anything model type