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DeMapGS: Simultaneous Mesh Deformation and Surface Attribute Mapping via Gaussian Splatting

Published: December 11, 2025 | arXiv ID: 2512.10572v1

By: Shuyi Zhou , Shengze Zhong , Kenshi Takayama and more

Potential Business Impact:

Makes 3D models look real and easy to change.

Business Areas:
Geospatial Data and Analytics, Navigation and Mapping

We propose DeMapGS, a structured Gaussian Splatting framework that jointly optimizes deformable surfaces and surface-attached 2D Gaussian splats. By anchoring splats to a deformable template mesh, our method overcomes topological inconsistencies and enhances editing flexibility, addressing limitations of prior Gaussian Splatting methods that treat points independently. The unified representation in our method supports extraction of high-fidelity diffuse, normal, and displacement maps, enabling the reconstructed mesh to inherit the photorealistic rendering quality of Gaussian Splatting. To support robust optimization, we introduce a gradient diffusion strategy that propagates supervision across the surface, along with an alternating 2D/3D rendering scheme to handle concave regions. Experiments demonstrate that DeMapGS achieves state-of-the-art mesh reconstruction quality and enables downstream applications for Gaussian splats such as editing and cross-object manipulation through a shared parametric surface.

Country of Origin
🇯🇵 Japan

Page Count
14 pages

Category
Computer Science:
Graphics