Image restoration technology is a crucial field in image processing and is extensively utilized
across various domains. Recently, with advancements in graph convolutional network …

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 …

Mesh denoising (MD) is a critical task in geometry processing as meshes from scanning or
AIGC techniques are susceptible to noise contamination. The challenge of MD lies in the …

Mesh denoising is a fundamental yet challenging task. Most of the existing data‐driven
methods only consider the zero‐order information (vertex location) and first‐order …

Background and Objective A detailed representation of the airway geometry in the
respiratory system is critical for predicting precise airflow and pressure behaviors in …

Mesh denoising, aimed at removing noise from input meshes while preserving their feature
structures, is a practical yet challenging task. Despite the remarkable progress in learning …

Denoising diffusion models have shown a powerful capacity for generating high-quality
image samples by progressively removing noise. Inspired by this, we present a diffusion …

This work elaborates an innovative mesh denoising approach that combines feature
recovery and denoising in an alternating manner. It proposes a feature-driven variational …

Abstract 3D mesh denoising is a crucial pre-processing step in many graphics applications.
However, existing data-driven mesh denoising models, primarily trained on synthetic white …

Mesh denoising is a crucial research topic in geometric processing, as it is widely used in
reverse engineering and 3D modeling. The main objective of denoising is to eliminate noise …