Campus3D

The Point Cloud Dataset for

Building Reconstruction
Object Recognition

Li, Xinke, et al. "Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scene." Proceedings of the 28th ACM International Conference on Multimedia. 2020.

The features of Campus3D

The Campus3D provides a large-scale 3D point cloud dataset of NUS campus and a comprehensive learning benchmark for visual recognition, scene understanding and varies kinds of vision problems.

Large Scale

This dataset was generated from unmanned aerial vehicle photography and covers 1.58 square km area of National University of Singapore campus. It consists of around 1 billion points.

Fully Labelled

Each point is annotated by a hierarchical and instance-based label. There are 2,530 modality-based instances, 24 semantic classes and 6 pattern-based regions.

Multi Functional

This dataset can be used for object detection, semantic segmentation, instance segmentation, fast scene understanding, object detection, 3D model reconstruction and etc.