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DMesh: A Differentiable Mesh Representation

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arxiv 2404.13445 v3 pith:OLXZ3KKB submitted 2024-04-20 cs.CV cs.GR

Sanghyun Son , Matheus Gadelha , Yang Zhou , Zexiang Xu , Ming C. Lin , Yi Zhou This is my paper · ORCID
classification cs.CVcs.GR
keywords differentiabledmeshmeshfacesmeshesrepresentationtetrahedratriangular
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We present a differentiable representation, DMesh, for general 3D triangular meshes. DMesh considers both the geometry and connectivity information of a mesh. In our design, we first get a set of convex tetrahedra that compactly tessellates the domain based on Weighted Delaunay Triangulation (WDT), and select triangular faces on the tetrahedra to define the final mesh. We formulate probability of faces to exist on the actual surface in a differentiable manner based on the WDT. This enables DMesh to represent meshes of various topology in a differentiable way, and allows us to reconstruct the mesh under various observations, such as point cloud and multi-view images using gradient-based optimization. The source code and full paper is available at: https://sonsang.github.io/dmesh-project.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. A Hybrid Neural-Microfacet BRDF Model for Real-Time Rendering

    cs.GR 2026-08 conditional novelty 6.0 of 10

    A hybrid BRDF model, combining a GGX analytical term with a tiny learned residual and gating network, fits measured materials more accurately than fully neural models at equal memory cost.

  2. LATO.2: Factorized 3D Mesh Generation with Vertex and Topology Flow

    cs.GR 2026-07 conditional novelty 6.0 of 10

    LATO.2 factorizes mesh generation into a vertex-generation flow and a vertex-conditioned connectivity flow, beating joint-latent and autoregressive baselines on geometric fidelity and connectivity quality.

  3. DMesh++: An Efficient Differentiable Mesh for Complex Shapes

    cs.CV 2024-12 conditional novelty 6.0 of 10

    DMesh++ speeds up differentiable mesh generation by using a Minimum-Ball condition instead of weighted Delaunay triangulation, enabling faster reconstruction of complex shapes.

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