关键词: 深度学习, 点云标注, 语义分割

Abstract: Point cloud segmentation is a key technology in point cloud data understanding, but traditional algorithms cannot perform real-time semantic segmentation. In recent years, deep learning has applied on point cloud segmentation and achieved significant progress. This paper reviews the latest work of point cloud segmentation based on deep learning in the past four years. In line with main content, it is divided into five kind of methods： view-based and projection-based method, volumetric method, unordered point cloud method, ordered point cloud method and unsupervised deep learning method, meanwhile it givs a brief review. Finally, the paper analyzes the advantages and disadvantages of various methods and looks forward to future research trends.

Key words: deep learning, point cloud labeling, semantic segmentation