SUM is a new benchmark dataset of semantic urban meshes which covers about 4 km2 in Helsinki (Finland), with six classes: Ground, Vegetation, Building, Water, Vehicle, and Boat.
The authors used Helsinki 3D textured meshes as input and annotated them as a benchmark dataset of semantic urban meshes. The Helsinki's raw dataset covers about 12 km2 and was generated in 2017 from oblique aerial images that have about a 7.5 cm ground sampling distance (GSD) using an off-the-shelf commercial software namely ContextCapture.
The entire region of Helsinki is split into tiles, and each of them covers about 250 m2.
Image source: Gao et al.