Point cloud is a widely used 3D data form, which can be produced by depth sensors, such
as Light Detection and Ranging (LIDAR) and RGB-D cameras. Being unordered and …

Over the past decade deep learning has driven progress in 2D image understanding.
Despite these advancements, techniques for automatic 3D sensed data understanding, such …

Triangular meshes have been actively used in computer graphics to represent 3D shapes.
However, due to their non-uniform and irregular nature, learning such data with a Deep …

In the computer vision field, many 3D deep learning models that directly manage 3D point
clouds (proposed after PointNet) have been published. Moreover, deep learning-based …

Deep learning methods have been successfully applied to image processing, mainly using
2D vision sensors. Recently, the rise of depth cameras and other similar 3D sensors has …

Point set is a major type of 3D structure representation format characterized by its data
availability and compactness. Most former deep learning-based point set models pay equal …

Point cloud classification plays a significant role in Light Detection and Ranging (LiDAR)
applications. However, most available multi-scale feature learning networks for large-scale …

A key question in the problem of 3D reconstruction is how to train a machine or a robot to
model 3D objects. Many tasks like navigation in real-time systems such as autonomous …