A Benchmark Dataset of Semantic Urban Meshes (SUM)
"A Benchmark Dataset of Semantic Urban Meshes (SUM)", Weixiao Gao, Hugo Ledoux, Liangliang Nan & Jantien Stoter
We introduce a new benchmark dataset of semantic urban meshes which covers about 4 km2 in Helsinki (Finland), with six classes: Terrain, Vegetation, Building, Water, Vehicle, and Boat.
We have 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. As shown in the figures below, we have selected the central region of Helsinki as the study area, which includes 64 tiles.