# Nonwatertight Mesh Reconstruction

Source: [Nonwatertight Mesh Reconstruction](<https://www.sota2.com/research/paper/68fa6ce21e209131cea367cd>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T00:20:37.261Z

Authors: Partha Ghosh

Published: 2022-06-26T19:53:00.000Z

## Abstract

Reconstructing 3D non-watertight mesh from an unoriented point cloud is an unexplored area in computer vision and computer graphics. In this project, we tried to tackle this problem by extending the learning-based watertight mesh reconstruction pipeline presented in the paper 'Shape as Points'. The core of our approach is to cast the problem as a semantic segmentation problem that identifies the region in the 3D volume where the mesh surface lies and extracts the surfaces from the detected regions. Our approach achieves compelling results compared to the baseline techniques.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2206.12952>)

[PDF](<https://arxiv.org/pdf/2206.12952.pdf>)