MeshSplatting: Differentiable Rendering with Opaque Meshes

• URL: http://arxiv.org/abs/2512.06818v1
• Date: Sun, 07 Dec 2025 12:31:04 GMT
• Title: MeshSplatting: Differentiable Rendering with Opaque Meshes
• Authors: Jan Held, Sanghyun Son, Renaud Vandeghen, Daniel Rebain, Matheus Gadelha, Yi Zhou, Anthony Cioppa, Ming C. Lin, Marc Van Droogenbroeck, Andrea Tagliasacchi,
• Abstract summary: We present MeshSplatting, a mesh-based reconstruction approach that jointly optimize geometry and appearance through differentiable rendering.<n>On Mip-NeRF360, it boosts PSNR by +0.69 dB over the current state-of-the-art MiLo for mesh-based novel view synthesis.
• Score: 59.240722437975755
• License: http://creativecommons.org/licenses/by/4.0/
• 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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