计算机工程与应用2020，Vol.56Issue(1)：38-45,8.DOI:10.3778/j.issn.1002-8331.1910-0157
基于深度学习的点云分割方法综述
Deep Learning Based Point Cloud Segmentation: A Survey
摘要
Abstract
Point cloud segmentation is a key technology in point cloud data understanding, but traditional algorithms can-not 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.关键词
深度学习/点云标注/语义分割Key words
deep learning/point cloud labeling/semantic segmentation分类
信息技术与安全科学引用本文复制引用
俞斌,董晨,刘延华,程烨..基于深度学习的点云分割方法综述[J].计算机工程与应用,2020,56(1):38-45,8.基金项目
国家自然科学基金(No.61672159) （No.61672159）
福建省自然科学基金(No.2018J01793) （No.2018J01793）
福建省教育厅项目(No.JAT170099). （No.JAT170099）
