Semantic Segmentation for Point Cloud Scenes via Dilated Graph Feature Aggregation and Pyramid Decoders. (arXiv:2204.04944v3 [cs.CV] UPDATED)

Semantic segmentation of point clouds generates comprehensive understanding
of scenes through densely predicting the category for each point. Due to the
unicity of receptive field, semantic segmentation of point clouds remains
challenging for the expression of multi-receptive field features, which brings
about the misclassification of instances with similar spatial structures. In
this paper, we propose a graph convolutional network DGFA-Net rooted in dilated
graph feature aggregation (DGFA), guided by multi-basis aggregation loss
(MALoss) calculated through Pyramid Decoders. To configure multi-receptive …

aggregation arxiv cloud feature graph segmentation semantic