RadarScenes is a real-world radar point cloud dataset for automotive applications.

It consists of measurements and point-wise annotations from more than four hours of driving collected by four series radar sensors mounted on one test vehicle. Individual detections of dynamic objects were manually grouped to clusters and labeled afterwards. The purpose of this data set is to enable the development of novel (machine learning-based) radar perception algorithms with the focus on moving road users. Images of the recorded sequences were captured using a documentary camera.