Color guided convolutional network for point cloud semantic segmentation

Color guided convolutional network for point cloud semantic segmentation

Blog Article

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, Autres 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 Energy Support selecting unit.Experimental results and comparisons with recent methods demonstrate the superiority of our approach.