Continuous conditional random field convolution for point cloud segmentation

•A continuous CRF graph convolution (CRFConv) is proposed to model the upsampling process of point cloud features.•A point cloud segmentation network based on the CRFConv is built to enhance the location ability of the network.•The classical discrete CRF is also reformulated as an additional graph convolution to refine the labels.•A dual CRF network is implemented to model the data affinity in both feature space and label space simultaneously.•The experiments on various challenging benchmarks demonstrate the effectiveness and robustness of the proposed method.