This article presents a deep normal filtering network, called DNF-Net, for mesh denoising. To
better capture local geometry, our network processes the mesh in terms of local patches …

We propose a robust normal estimation method for both point clouds and meshes using a
low rank matrix approximation algorithm. First, we compute a local isotropic structure for …

In this paper, we propose a fast and efficient explicit three-dimensional (3D) mesh denoising
algorithm that utilizes the Allen–Cahn (AC) equation with a fidelity term. The phase-field …

This paper presents a simple and effective two-stage mesh denoising algorithm, where in
the first stage, face normal filtering is done by using bilateral normal filtering in a robust …

Mesh denoising is a fundamental problem in digital geometry processing. It seeks to remove
surface noise while preserving surface intrinsic signals as accurately as possible. While …

Recent studies have shown that the Total Generalized Variation (TGV) is highly effective in
preserving sharp features as well as smooth transition variations for image processing tasks …

This paper presents a non‐local low‐rank normal filtering method for mesh denoising. By
exploring the geometric similarity between local surface patches on 3D meshes in the form …

Mesh denoising is an essential geometric processing step for raw meshes generated by 3D
scanners and depth cameras. It is intended to remove noise while preserving surface …

Distinguishing between geometric features and noise is of paramount importance for mesh
denoising. In this paper, a graph-based feature-preserving mesh normal filtering scheme is …

Mesh denoising is a critical technology in geometry processing that aims to recover high-
fidelity 3D mesh models of objects from noise-corrupted versions. In this work, we propose a …