  We achieve 3D semantic scene labeling by exploring semantic relation between
each point and its contextual neighbors through edges. Besides an
encoder-decoder branch for predicting point labels, we construct an edge branch
to hierarchically integrate point features and generate edge features. To
incorporate point features in the edge branch, we establish a hierarchical
graph framework, where the graph is initialized from a coarse layer and
gradually enriched along the point decoding process. For each edge in the final
graph, we predict a label to indicate the semantic consistency of the two
connected points to enhance point prediction. At different layers, edge
features are also fed into the corresponding point module to integrate
contextual information for message passing enhancement in local regions. The
two branches interact with each other and cooperate in segmentation. Decent
experimental results on several 3D semantic labeling datasets demonstrate the
effectiveness of our work.
