DALES (DALES: A Large-scale Aerial LiDAR Data Set for Semantic Segmentation)

We present the Dayton Annotated LiDAR Earth Scan (DALES) data set, a new large-scale aerial LiDAR data set with over a half-billion hand-labeled points spanning 10 square kilometers of area and eight object categories. Large annotated point cloud data sets have become the standard for evaluating deep learning methods. However, most of the existing data sets focus on data collected from a mobile or terrestrial scanner with few focusing on aerial data. Point cloud data collected from an Aerial Laser Scanner (ALS) presents a new set of challenges and applications in areas such as 3D urban modeling and large-scale surveillance. DALES is the most extensive publicly available ALS data set with over 400 times the number of points and six times the resolution of other currently available annotated aerial point cloud data sets. This data set gives a critical number of expert verified hand-labeled points for the evaluation of new 3D deep learning algorithms, helping to expand the focus of curren

代顿标注激光雷达地表扫描（Dayton Annotated LiDAR Earth Scan, DALES）数据集是一款新型大规模机载激光雷达数据集，包含超5亿个人工标注点，覆盖10平方公里范围，涵盖8类目标类别。大型标注点云数据集已成为评估深度学习方法的标准基准。然而当前主流公开数据集多聚焦于移动或地面激光扫描仪采集的数据，针对机载激光雷达数据的标注数据集相对匮乏。机载激光扫描（Aerial Laser Scanner, ALS）所获取的点云数据，在3D城市建模、大规模安防监控等领域带来了全新的应用场景与技术挑战。DALES是目前规模最大的公开机载激光扫描点云标注数据集，其点云数量为现有同类公开标注数据集的400余倍，分辨率更是其6倍。本数据集提供了经专家核验的海量人工标注点，可用于新型3D深度学习算法的评估工作，助力拓展当前研究的聚焦方向（原文此处存在截断）