Point cloud registration is an important task in computer vision, where the goal is to estimate
a transformation to align a pair of point clouds. Most of the existing registration methods face …

3D point clouds have found a wide variety of applications in multimedia processing, remote
sensing, and scientific computing. Although most point cloud processing systems are …

The quality of point clouds is often limited by noise introduced during their capture process.
Consequently, a fundamental 3D vision task is the removal of noise, known as point cloud …

Over the past decade, we have witnessed an enormous amount of research effort dedicated
to the design of point cloud denoising techniques. In this article, we first provide a …

Convolution on 3D point clouds is widely researched yet far from perfect in geometric deep
learning. The traditional wisdom of convolution characterises feature correspondences …

Since 2021, the term" Metaverse" has been the most popular one, garnering a lot of interest.
Because of its contained environment and built-in computing and networking capabilities, a …

The captured 3D point clouds by depth cameras and 3D scanners are often corrupted by
noise, so point cloud denoising is typically required for downstream applications. We …

Point cloud filtering is a fundamental 3D vision task which aims to remove noise while
recovering the underlying clean surfaces. State-of-the-art methods remove noise by moving …

摘要随着传感器技术的不断发展, 三维点云被广泛应用于自动驾驶, 机器人, 遥感, 文物修复,
增**现实, 虚拟现实等领域的视觉任务中. 然而, 直接应用收集到的海量原始点云数据得到的效果 …

Point cloud filtering, the main bottleneck of which is removing noise (outliers) while
preserving geometric features, is a fundamental problem in 3D field. The two-step schemes …