This paper presents a view-guided solution for the task of point cloud
completion. Unlike most existing methods directly inferring the missing points
using shape priors, we address this task by introducing ViPC (
Point cloud completion using a self-supervised framework called Partial2Complete (P2C) that utilizes incomplete point clouds to predict masked patches by learning prior information from different partial objects, incorporating a region-aware chamfer distance and a normal consistency constraint, and demonstrating comparable results to methods trained with complete shapes.