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NeurIPS 2024PosterAccept (poster)

DMesh: A Differentiable Mesh Representation

Sanghyun Son, Matheus Gadelha, Yang Zhou, Zexiang Xu, Ming Lin, Yi Zhou

University of Maryland, College Park · Adobe Systems · Adobe Research · University of Maryland - College Park

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摘要

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 clouds and multi-view images using gradient-based optimization. We publicize the source code and supplementary material at our project page (https://sonsang.github.io/dmesh-project).