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UrbanScene3D: A Large Scale Urban Scene Dataset and Simulator

by   Yilin Liu, et al.

The ability to perceive the environments in different ways is essential to robotic research. This involves the analysis of both 2D and 3D data sources. We present a large scale urban scene dataset associated with a handy simulator based on Unreal Engine 4 and AirSim, which consists of both man-made and real-world reconstruction scenes in different scales, referred to as UrbanScene3D. Unlike previous works that purely based on 2D information or man-made 3D CAD models, UrbanScene3D contains both compact man-made models and detailed real-world models reconstructed by aerial images. Each building has been manually extracted from the entire scene model and then has been assigned with a unique label, forming an instance segmentation map. The provided 3D ground-truth textured models with instance segmentation labels in UrbanScene3D allow users to obtain all kinds of data they would like to have: instance segmentation map, depth map in arbitrary resolution, 3D point cloud/mesh in both visible and invisible places, etc. In addition, with the help of AirSim, users can also simulate the robots (cars/drones)to test a variety of autonomous tasks in the proposed city environment. Please refer to our paper and website( for further details and applications.


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