Swiss3DCities: Aerial Photogrammetric 3D Pointcloud Dataset with Semantic Labels

We introduce a new outdoor urban 3D pointcloud dataset, covering a total area of 2.7 km², sampled from three Swiss cities with different characteristics. The dataset is manually annotated for semantic segmentation with per-point labels, and is built using photogrammetry from images acquired by multirotors equipped with high-resolution cameras.  In contrast to datasets acquired with ground LiDAR sensors, the resulting point clouds are uniformly dense and complete, and are useful to disparate applications, including autonomous driving, gaming, smart city planning, and robotics.