Abstract:
Previous Point Cloud semantic segmentation methods lack the ability to fully
capture the feature representation of the overlapping areas of different classes.
Some works have identified the edge detection problem but they ignored the
inner points of the objects in the scene. This research has applied an aggre gation strategy which processed features from same class and different classes
equally. Each neighbor of the feature is identified first, if it belongs to the
same class as the feature or a different class from the feature. These features
are then dealt by two specific modules. We applied this strategy on semantic
segmentation network to improve segmentation results. The results section
proves the effectiveness of this methodology.
