Capturing, Reconstructing, and Simulating: The UrbanScene3D Dataset

We present UrbanScene3D, a large-scale data platform for research of urban scene perception and reconstruction. UrbanScene3D contains over 128k high-resolution images covering 16 scenes including large-scale real urban regions and synthetic cities with 136 km(2) area in total. The dataset also contains high-precision LiDAR scans and hundreds of image sets with different observation patterns, which provide a comprehensive benchmark to design and evaluate aerial path planning and 3D reconstruction algorithms. In addition, the dataset, which is built on Unreal Engine and Airsim simulator together with the manually annotated unique instance label for each building in the dataset, enables the generation of all kinds of data, e.g., 2D depth maps, 2D/3D bounding boxes, and 3D point cloud/mesh segmentations, etc. The simulator with physical engine and lighting system not only produce variety of data but also enable users to simulate cars or drones in the proposed urban environment for future research. The dataset with aerial path planning and 3D reconstruction benchmark is available at: https://vcc.tech/UrbanScene3D.

Automated summary

UrbanScene3D is a large-scale data platform for research on urban scene perception and reconstruction. It includes a vast collection of high-resolution images, LiDAR scans, and image sets with various observation patterns. The dataset provides a comprehensive benchmark for designing and evaluating aerial path planning and 3D reconstruction algorithms. Additionally, the simulator with a physical engine and lighting system allows for simulating vehicles or drones in the proposed urban environment for future research.