Fig. 11
From: Frame points attention convolution for deep learning on point cloud
Visualization of FPA convolutional filter weights. The first row shows the filter weights generated by FPA, while the second row displays those obtained through linear interpolation (LI). The color of each point represents the spatial convolutional weight generated by FPA, with the color scale indicating the magnitude of the weight: warmer colors (closer to red) correspond to larger weight values, signifying a stronger ability to extract shape features from those points. Larger points represent the frame points, specifically the 8 vertices and the center point of the hexahedron. The similarity in color between a point and the frame points reflects the degree of attention the convolutional weights assign to those frame points.
