In recent years, 3D laser scanning technology has been applied to tunnel engineering.
Although more intelligent than traditional measurement technology, it is still challenging to …

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 …

Point cloud filtering is a fundamental problem in geometry modeling and processing.
Despite of significant advancement in recent years, the existing methods still suffer from two …

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 …

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 …

This paper presents a neural network for robust normal estimation on point clouds, named
AdaFit, that can deal with point clouds with noise and density variations. Existing works use …

We propose a novel normal estimation method called HSurf-Net, which can accurately
predict normals from point clouds with noise and density variations. Previous methods focus …

Feature lines are important geometric cues in characterizing the structure of a CAD model.
Despite great progress in both explicit reconstruction and implicit reconstruction, it remains a …