Mesh Denoising with Facet Graph Convolutions-Reference-Cited by-同舟云学术

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Mesh Denoising with Facet Graph Convolutions

Published:2020 Issue: Volume: Page:1-1
ISSN:1077-2626
Container-title:IEEE Transactions on Visualization and Computer Graphics
language:
Short-container-title:IEEE Trans. Visual. Comput. Graphics

Author:

Armando Matthieu,Franco Jean-Sebastien,Boyer Edmond

Funder

Microsoft Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

http://xplorestaging.ieee.org/ielx7/2945/4359476/09296808.pdf?arnumber=9296808

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A fast, efficient, and explicit phase-field model for 3D mesh denoising;Applied Mathematics and Computation;2023-12

2. Curvature‐driven Multi‐stream Network for Feature‐preserving Mesh Denoising;Computer Graphics Forum;2023-11-23

3. Geometric and Learning-Based Mesh Denoising: A Comprehensive Survey;ACM Transactions on Multimedia Computing, Communications, and Applications;2023-11-10

4. A Multi-Stream Network for Mesh Denoising Via Graph Neural Networks with Gaussian Curvature;2023 IEEE International Conference on Image Processing (ICIP);2023-10-08

5. Feature preserving 3D mesh denoising with a Dense Local Graph Neural Network;Computer Vision and Image Understanding;2023-08

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