Laplacian Mesh Processing

By Olga Sorkine-Hornung. Eurographics, 2005

300 citations recorded by the source corpus.

Subfields: Archeology, Computational Mechanics, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/3ae1e9b3e39cc8c6e51ef9a36954051845e18d3c

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In Archeology

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Citations in the corpus

Multi-Garment Net: Learning to Dress 3D People From Images (2019, methodology): “In order to globally deform the template to match the clothing boundaries in a single shot, we define an objective function based on Laplacian deformation [56].”
NeRF-Editing: Geometry Editing of Neural Radiance Fields (2022, methodology): “Traditional mesh deformation methods are based on Laplacian coordinates [35, 57, 58], Poisson equation [79], and dual Laplacian coordinates [2].”
User-Friendly Interactive Image Segmentation Through Unified Combinatorial User Inputs (2010, background): “The first term in (10) is adapted from the Laplacian mesh processing [25] to preserve the global shape with the transform matrix defined as”
Extracting Triangular 3D Models, Materials, and Lighting From Images (2021, methodology): “Laplacian Regularizer In the second pass, when topology is locked, we use a Laplacian regularizer [63] on the triangle mesh to regularize the vertex movements.”
Modular primitives for high-performance differentiable rendering (2020, methodology): “Because of this, we apply a mesh Laplacian regularization term that penalizes local curvature changes compared to the base mesh.”
Graph Laplacians and their Convergence on Random Neighborhood Graphs (2006, background): “Sorkine (2005). If one has gathered points of a curved object with a laser scanner it is likely that the points have a non-uniform distribution on the object.”
On Linear Variational Surface Deformation Methods (2008, background): “In practice, rotations of up to =2 can be well performed [57].”