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 Right Link Arm 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 Salt Rifles 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.