Annotated point clouds of buildings: a segmented dataset of single-family houses

The dataset contains 2.904 geometries of single-family houses in the form of annotated Point Clouds, and was developed in order to train 3D Generative Adversarial Networks with architecturally relevant data. More specificaly the geometries are segmented within 3 classes: wall, roof, floor. The points of the point clouds are saved in .pts files while their labels are saved in .seg files.

本数据集包含2904个带标注的单户住宅点云（Point Clouds）几何模型，旨在依托建筑相关数据训练3D生成对抗网络（3D Generative Adversarial Networks）。更具体而言，该数据集的几何模型被划分为3个类别：墙体、屋顶与地面。点云的坐标点存储于.pts格式文件中，其对应的标注标签则存储于.seg格式文件内。