Generated realistic noise and rotation-equivariant models for data-driven mesh denoising-Reference-Cited by-同舟云学术

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Generated realistic noise and rotation-equivariant models for data-driven mesh denoising

Published:2024-06 Issue: Volume:111 Page:102306
ISSN:0167-8396
Container-title:Computer Aided Geometric Design
language:en
Short-container-title:Computer Aided Geometric Design

Author:

Yang Sipeng^ORCID,Ren Wenhui,Zeng Xiwen,Zhu Qingchuan,Fu Hongbo,Fan Kaijun,Yang Lei,Yu Jingping,Kou Qilong,Jin Xiaogang^ORCID

Publisher

Elsevier BV

Reference47 articles.

1. Mesh denoising with facet graph convolutions;Armando;IEEE Trans. Vis. Comput. Graph.,2020

2. Learning to generate realistic noisy images via pixel-level noise-aware adversarial training;Cai;Adv. Neural Inf. Process. Syst.,2021

3. Geometric and learning-based mesh denoising: a comprehensive survey;Chen;ACM Trans. Multimed. Comput. Commun. Appl.,2023

4. Anisotropic geometric diffusion in surface processing;Clarenz,2000

5. Implicit fairing of irregular meshes using diffusion and curvature flow;Desbrun,1999

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