3D Point Cloud Representation Learning and Reconstruction using Vector-based Neural Network

Abstract

3D point cloud learning using deep learning architecture has become an active research trend due to advancement in 3D acquisition technologies. However, raw point clouds are often incomplete, unstructured, and noisy due to viewpoint occlusion and surface irregularity. 3D modeling task is the focus in this research work for 3D point cloud representation learning and reconstruction due to its importance in vast applications that require a concise and efficient reconstruction and recognition of object model.