A Survey on Deep Learning Based Segmentation, Detection and Classification for 3D Point Clouds

The computer vision, graphics, and machine learning research groups have given a significant amount of focus to 3D object recognition (segmentation, detection, and classification). Deep learning approaches have lately emerged as the preferred method for 3D segmentation problems as a result of their outstanding performance in 2D computer vision. As a result, many innovative approaches have been proposed and validated on multiple benchmark datasets. This study offers an in-depth assessment of the latest developments in deep learning-based 3D object recognition. We discuss the most well-known 3D object recognition models, along with evaluations of their distinctive qualities.

Automated summary

The computer vision, graphics, and machine learning research groups have focused on 3D object recognition. Deep learning approaches have become popular in this field due to their excellent performance in 2D computer vision. Many innovative methods have been proposed and evaluated on benchmark datasets. This study provides a comprehensive assessment of the latest developments in deep learning-based 3D object recognition, covering well-known models and their distinctive qualities.