# Voxel Structure-based Mesh Reconstruction from a 3D Point Cloud

arXiv: https://arxiv.org/abs/2104.10622 · HTML: https://mlsanity.com/paper/2104.10622/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 71 references that are in the map.
- First posted on arXiv 21 Apr 2021.

## Builds on (most cited first, 1 of 1)

- [Robust and High Fidelity Mesh Denoising](https://mlsanity.com/paper/1711.05341/) (2017)

## Built on by (most cited first, 7 of 7)

- [SurfPro: Functional Protein Design Based on Continuous Surface](https://mlsanity.com/paper/2405.06693/) (2024)
- [Efficient and Scalable Point Cloud Generation with Sparse Point-Voxel Diffusion Models](https://mlsanity.com/paper/2408.06145/) (2024)
- [NeuralMeshing: Differentiable Meshing of Implicit Neural Representations](https://mlsanity.com/paper/2210.02382/) (2022)
- [Target-Guided Bayesian Flow Networks for Quantitatively Constrained CAD Generation](https://mlsanity.com/paper/2510.25163/) (2025)
- [Disentangling Hippocampal Shape Variations: A Study of Neurological Disorders Using Mesh Variational Autoencoder with Contrastive Learning](https://mlsanity.com/paper/2404.00785/) (2024)
- [MUVOD: A Novel Multi-view Video Object Segmentation Dataset and A Benchmark for 3D Segmentation](https://mlsanity.com/paper/2507.07519/) (2025)
- [Curve Skeletonization in Continuous domain for Meshes and Point Clouds](https://mlsanity.com/paper/2605.25921/) (2026)

## Abstract (arXiv)

Mesh reconstruction from a 3D point cloud is an important topic in the fields of computer graphic, computer vision, and multimedia analysis. In this paper, we propose a voxel structure-based mesh reconstruction framework. It provides the intrinsic metric to improve the accuracy of local region detection. Based on the detected local regions, an initial reconstructed mesh can be obtained. With the mesh optimization in our framework, the initial reconstructed mesh is optimized into an isotropic one with the important geometric features such as external and internal edges. The experimental results indicate that our framework shows great advantages over peer ones in terms of mesh quality, geometric feature keeping, and processing speed.