NPM3D dataset with instance labels used in paper "Toward Accurate Instance Segmentation in Large-scale LiDAR Point Clouds"

NPM3D (https://npm3d.fr/paris-carla-3d) consists of mobile laser scanning (MLS) point clouds collected in four different regions in the French cities of Paris and Lille, where each point has been annotated with two labels: one that assigns it to one out of 10 semantic categories and another one that assigns it to an object instance. When inspecting the data, we found 9 cases where multiple tree instances had not been separated correctly (i.e., they had the same ground truth instance label). These cases were manually corrected using the CloudCompare software (https://www.cloudcompare.org), and 35 individual tree instances were obtained. Our variant of the dataset with 10 semantic categories and enhanced instance labels is publicly available.

NPM3D（访问地址：https://npm3d.fr/paris-carla-3d）包含了在法国巴黎与里尔两座城市的四个不同区域采集的移动激光扫描（mobile laser scanning, MLS）点云数据。该数据集的每个点均被赋予两类标注标签：一类用于将点划分至10个语义类别中的某一类，另一类则用于归属至对应物体实例。在对数据进行核查的过程中，我们发现存在9起多棵树木实例未被正确分离的情况（即这些实例拥有相同的真值实例标签）。针对上述问题，我们借助CloudCompare软件（访问地址：https://www.cloudcompare.org）完成了手动修正，最终得到35个独立的树木实例。本团队改造的该数据集版本保留了10个语义类别，并优化了实例标注，现已公开发布。