Mesh Density Adaptation for Template-based Shape Reconstruction
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Abstract (arXiv)
In 3D shape reconstruction based on template mesh deformation, a regularization, such as smoothness energy, is employed to guide the reconstruction into a desirable direction. In this paper, we highlight an often overlooked property in the regularization: the vertex density in the mesh. Without careful control on the density, the reconstruction may suffer from under-sampling of vertices near shape details. We propose a novel mesh density adaptation method to resolve the under-sampling problem. Our mesh density adaptation energy increases the density of vertices near complex structures via deformation to help reconstruction of shape details. We demonstrate the usability and performance of mesh density adaptation with two tasks, inverse rendering and non-rigid surface registration. Our method produces more accurate reconstruction results compared to the cases without mesh density adaptation.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 13 of its 46 references that are in the map. First posted on arXiv 30 Jul 2023.
Builds on
13 of 46 references.
References · 13
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 649
- 2020Modular Primitives for High-Performance Differentiable Renderingcited by 439
- 2017Neural 3D Mesh Renderercited by 437
- 20163D Menagerie: Modeling the 3D shape and pose of animalscited by 310
- 2019Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformationcited by 103
- 2021Unified Shape and SVBRDF Recovery using Differentiable Monte Carlo Renderingcited by 71
- 2017Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translationcited by 56
- 2020Point2Mesh: A Self-Prior for Deformable Meshescited by 41
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- 2022VectorAdam for Rotation Equivariant Geometry Optimizationcited by 17
- 20213DCaricShop: A Dataset and A Baseline Method for Single-view 3D Caricature Face Reconstructioncited by 16
1 more
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Citing papers per year: 2024: 3; 2025: 2; 2026: 2.
7 papers.
- 2024DDM: A Metric for Comparing 3D Shapes Using Directional Distance Fieldscited by 5
- 2024Semantic Human Mesh Reconstruction with Texturescited by 5
- 2025Neural Geometry Image-Based Representations with Optimal Transport (OT)cited by 2
- 2025Inverse Rendering for High-Genus Surface Meshes from Multi-View Imagescited by 2
- 2024Towards Geometric-Photometric Joint Alignment for Facial Mesh Registrationcited by 0
- 2026Inverse Rendering for High-Genus 3D Surface Meshes from Multi-view Images with Persistent Homology Priorscited by 0
- 2026RADmesh: Remesh-Aware Mesh Deformationcited by 0
- 2026RADmesh: Remesh-Aware Mesh Deformation17 Aug 2026
- 2026Inverse Rendering for High-Genus 3D Surface Meshes from Multi-view Images with Persistent Homology Priors17 Jan 2026
- 2025Inverse Rendering for High-Genus Surface Meshes from Multi-View Images24 Nov 2025
- 2025Neural Geometry Image-Based Representations with Optimal Transport (OT)24 Nov 2025
- 2024Towards Geometric-Photometric Joint Alignment for Facial Mesh Registration5 Mar 2024
- 2024Semantic Human Mesh Reconstruction with Textures5 Mar 2024
- 2024DDM: A Metric for Comparing 3D Shapes Using Directional Distance Fields18 Jan 2024