NormalNet: Learning-based Normal Filtering for Mesh Denoising

14 Nov 2019 Zhao Wenbo Liu Xianming Zhao Yongsen Fan Xiaopeng Zhao Debin

Mesh denoising is a critical technology in geometry processing that aims to recover high-fidelity 3D mesh models of objects from their noise-corrupted versions. In this work, we propose a learning-based normal filtering scheme for mesh denoising called NormalNet, which maps the guided normal filtering (GNF) into a deep network... (read more)

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Categories


  • GRAPHICS
  • COMPUTATIONAL GEOMETRY