MeshSplatting: Differentiable Rendering with Opaque Meshes

Jan Held, Sanghyun Son, Renaud Vandeghen, Daniel Rebain, Matheus Gadelha +5 more
12/7/2025
cs.CV

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Abstract

Primitive-based splatting methods like 3D Gaussian Splatting have revolutionized novel view synthesis with real-time rendering. However, their point-based representations remain incompatible with mesh-based pipelines that power AR/VR and game engines. We present MeshSplatting, a mesh-based reconstruction approach that jointly optimizes geometry and appearance through differentiable rendering. By enforcing connectivity via restricted Delaunay triangulation and refining surface consistency, MeshSplatting creates end-to-end smooth, visually high-quality meshes that render efficiently in real-time 3D engines. On Mip-NeRF360, it boosts PSNR by +0.69 dB over the current state-of-the-art MiLo for mesh-based novel view synthesis, while training 2x faster and using 2x less memory, bridging neural rendering and interactive 3D graphics for seamless real-time scene interaction. The project page is available at https://meshsplatting.github.io/.

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Cite this paper

@article{held2025meshsplatting,
  title  = {MeshSplatting: Differentiable Rendering with Opaque Meshes},
  author = {Jan Held and Sanghyun Son and Renaud Vandeghen and Daniel Rebain and Matheus Gadelha and Yi Zhou and Anthony Cioppa and Ming C. Lin and Marc Van Droogenbroeck and Andrea Tagliasacchi},
  year   = {2025},
  eprint = {2512.06818},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2512.06818v1}
}

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