The paper addresses the global shortage of detailed road surface data by leveraging street-view imagery from Mapillary and advanced deep learning techniques. Traditional datasets like OpenStreetMap (OSM) often lack comprehensive road surface attributes—with only about 30–40% coverage—hindering applications such as travel time estimation, disaster response routing, urban planning, and environmental assessments. To fill this gap, the paper proposes a novel approach that utilizes heterogen...
