Polygon Mesh Processing

By Mario Botsch, Leif Kobbelt, Mark Pauly, Pierre Alliez, Bruno Lévy. 2010

841 citations recorded by the source corpus.

Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/786aeea8903e20063a5fe24f3fa99cdc51e50e76

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In Computer Graphics and Computer-Aided Design

In Computer Vision and Pattern Recognition

Citations in the corpus

TailorNet: Predicting Clothing in 3D as a Function of Human Pose, Shape and Garment Style (2020, methodology): “= g i+ g i; (7) where g i is the discrete Laplace-Beltrami operator applied at vertex g i, and and the number of iterations control the level of smoothing. Eq.7is also known as Laplacian smoothing [12,7]. We use = 0:15 and 80 iterations, to obtain a smooth low-frequency mesh G^LF and a highfrequen”
GWCNN: A Metric Alignment Layer for Deep Shape Analysis (2017, positive): “For intrinsic per-point features f of deformable manifold meshes we use Gaussian curvature [BKP ∗ 10], conformal factor [BCG08] and the ﬁrst entry of the Wave Kernel Signature [ASC11].”
Projective dynamics (2014, methodology): “If S is a 2-manifold simplicial complex this energy can be discretized over triangles using a piecewise linear hat basis [Botsch et al. 2010].”
Online modeling for realtime facial animation (2013, methodology): “DE is the diagonal matrix of eigenvalues corresponding to the eigenvectors in E of the Laplacian matrix L [Botsch et al. 2010].”
MeshCNN: a network with an edge (2019, methodology): “Many of the operators that we present or use in our work are based on classic mesh processing techniques [Botsch et al. 2010], or more specifically, mesh simplification techniques [Garland and Heckbert 1997; Hoppe 1997; Hoppe et al. 1993].”
3D Skeletons: A State‐of‐the‐Art Report (2016, background): “Explicit , (surface) representations capture the interface between shape interior and exterior, based on various sampling and reconstruction schemes, e.g. , point clouds or polygon meshes [BKP ∗ 10, Ago05].”
Moser Flow: Divergence-based Generative Modeling on Manifolds (2021, methodology): “We will use the standard (cotangent) discretization of the Laplacian over meshes (Botsch et al., 2010).”
Computational Optimal Transport (2018, background): “A typical example is when using piecewise linear finite elements, so that L is the celebrated cotangent Laplacian (see [Botsch et al., 2010] for a detailed account for this construction).”