PaMO: Parallel Mesh Optimization for Intersection-Free Low-Poly Modeling on the GPU
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Abstract (arXiv)
Reducing the triangle count in complex 3D models is a basic geometry preprocessing step in graphics pipelines such as efficient rendering and interactive editing. However, most existing mesh simplification methods exhibit a few issues. Firstly, they often lead to self-intersections during decimation, a major issue for applications such as 3D printing and soft-body simulation. Second, to perform simplification on a mesh in the wild, one would first need to perform re-meshing, which often suffers from surface shifts and losses of sharp features. Finally, existing re-meshing and simplification methods can take minutes when processing large-scale meshes, limiting their applications in practice. To address the challenges, we introduce a novel GPU-based mesh optimization approach containing three key components: (1) a parallel re-meshing algorithm to turn meshes in the wild into watertight, manifold, and intersection-free ones, and reduce the prevalence of poorly shaped triangles; (2) a robust parallel simplification algorithm with intersection-free guarantees; (3) an optimization-based safe projection algorithm to realign the simplified mesh with the input, eliminating the surface shift introduced by re-meshing and recovering the original sharp features. The algorithm demonstrates remarkable efficiency, simplifying a 2-million-face mesh to 20k triangles in 3 seconds on RTX4090. We evaluated the approach on the Thingi10K dataset and showcased its exceptional performance in geometry preservation and speed.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Sep 2025.
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Citing papers per year: 2025: 1; 2026: 4.
5 papers.
- 2025PartUV: Part-Based UV Unwrapping of 3D Meshescited by 9
- 2026Emerging Extrinsic Dexterity in Cluttered Scenes via Dynamics-aware Policy Learningcited by 2
- 2026TopoMesh: High-Fidelity Mesh Autoencoding via Topological Unificationcited by 2
- 2026AssetGen: Deployable 3D Asset Generation at Interactive Speedcited by 2
- 2026LUCID: An Agentic AI Framework on Digital-Twin in the Loop for QoS-Guaranteeing Robotic Controlcited by 1
- 2026LUCID: An Agentic AI Framework on Digital-Twin in the Loop for QoS-Guaranteeing Robotic Control28 Aug 2026
- 2026AssetGen: Deployable 3D Asset Generation at Interactive Speed22 May 2026
- 2026TopoMesh: High-Fidelity Mesh Autoencoding via Topological Unification25 Mar 2026
- 2026Emerging Extrinsic Dexterity in Cluttered Scenes via Dynamics-aware Policy Learning10 Mar 2026
- 2025PartUV: Part-Based UV Unwrapping of 3D Meshes20 Nov 2025