基于深度学习的点云语义分割研究综述.

PointCloud is an important type of 3D data that is widely used in artificial intelligence applications such as autonomous driving, robotics, virtual and augmented reality. Point cloud semantic segmentation is a key task in point cloud processing, which aims to assign each point in the point cloud to a specific semantic category. This paper reviews the research progress of deep learning-based point cloud semantic segmentation in domestic and foreign studies. Firstly, commonly used open source datasets in point cloud semantic segmentation are summarized, and both indirect and direct deep learning processing methods based on point cloud are introduced along with their application progress. Additionally, the experimental results of these methods are presented and briefly compared. Finally, the problems in current point cloud semantic segmentation are discussed, and future research directions are proposed. [ABSTRACT FROM AUTHOR]