Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (23): 18-26.DOI: 10.3778/j.issn.1002-8331.2107-0142

• Research Hotspots and Reviews • Previous Articles     Next Articles

Research of Deep Learning-Based Semantic Segmentation for 3D Point Cloud

WANG Tao, WANG Wenju, CAI Yu   

  1. University of Shanghai for Science and Technology, Shanghai 200093, China
  • Online:2021-12-01 Published:2021-12-02



  1. 上海理工大学,上海 200093


This paper summarizes the methods of deep learning-based semantic segmentation for 3D point cloud. The literature research method is used to describe deep learning-based semantic segmentation methods for 3D point cloud according to the representation of data. It discusses the current situation of domestic and foreign development in recent years, and analyzes the advantages and disadvantages of the current related methods, and prospects the future development trend. Deep learning plays an extremely important role in the research of semantic segmentation technology for point cloud, and promotes the manufacturing, packaging fields and etc to development in the direction of intelligence. According to the advantages and disadvantages of various methods, it is an important research direction to construct a framework model of semantic segmentation combined with 2D-3D for projection, voxel, multi-view and point cloud in the future.

Key words: computer vision, intelligent packaging, deep learning, 3D point cloud, semantic segmentation



关键词: 计算机视觉, 智能包装, 深度学习, 三维点云, 语义分割