Flattening-Net: Deep Regular 2D Representation for 3D Point Cloud Analysis
Flattening-Net: Deep Regular 2D Representation for 3D Point Cloud Analysis
Point clouds are characterized by irregularity and unstructuredness, which pose challenges in efficient data exploitation and discriminative feature extraction. In this paper, we present an unsupervised deep neural architecture called Flattening-Net to represent irregular 3D point clouds of arbitrary geometry and topology as a completely regular 2D point geometry image …