Multiscale Receptive Fields Graph Attention Network for Point Cloud Classification

Figure 1

A typical framework of a 3D point cloud classification process. The model takes points in -dimensional space as its input and then extracts point features of dimension , followed by an aggregation module used to form a feature vector which is invariant to point permutation. Finally, a classifier is used to classify the resulting feature vector into categories.