RIConv++: Effective rotation invariant convolutions for 3D point clouds deep learning

• Main Authors: ZHANG, Zhiyuan, HUA, Binh-Son, YEUNG, Sai-Kit
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: 3D Point Cloud; Convolutional Neural; Networks; Deep Learning; Rotation Invariance; Artificial Intelligence and Robotics; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/7933; https://ink.library.smu.edu.sg/context/sis_research/article/8936/viewcontent/2202.13094.pdf
• Institution: Singapore Management University

3D point clouds deep learning is a promising field of research that allows a neural network to learn features of point clouds directly, making it a robust tool for solving 3D scene understanding tasks. While recent works show that point cloud convolutions can be invariant to translation and point pe...