Color guided convolutional network for point cloud semantic segmentation. (17th May 2022)

• Record Type: Journal Article
• Authors: Yang, Jing; Li, Haozhe; Jiang, Zhou; Zhang, Dong; Yue, Xiaoli; Du, Shaoyi
• Is Part Of: International journal of advanced robotic systems. Volume 19:Number 3(2022)
• Publication Date: 2022-05-17
• Subjects: Point cloud semantic segmentation -- deep learning -- color information -- color guided convolution; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/17298806221098506
• Languages: English
• ISSNs: 1729-8806

Abstract

Point cloud semantic segmentation based on deep learning methods is still a challenge due to the irregularity of structures and uncertainty of sampling. Color information often contains a lot of prior information, whereas the existing methods do not attach more importance to it. To deal with this problem, we propose a novel hard attention mechanism, named color-guided convolution. This convolution operator learns the correlation between geometric and color information by reordering the local points with color-indicated vectors. In addition, the global feature fusion is proposed to rectify features selected by the feature selecting unit. Experimental results and comparisons with recent methods demonstrate the superiority of our approach.