# Surface Reconstruction from 3D Line Segments

arXiv: https://arxiv.org/abs/1911.00451 · HTML: https://mlsanity.com/paper/1911.00451/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Nov 2019.

## Built on by (most cited first, 6 of 6)

- [PlaneTR: Structure-Guided Transformers for 3D Plane Recovery](https://mlsanity.com/paper/2107.13108/) (2021)
- [PlanarSplatting: Accurate Planar Surface Reconstruction in 3 Minutes](https://mlsanity.com/paper/2412.03451/) (2024)
- [Learning to Construct 3D Building Wireframes from 3D Line Clouds](https://mlsanity.com/paper/2208.11948/) (2022)
- [Improving Transformer Based Line Segment Detection with Matched Predicting and Re-ranking](https://mlsanity.com/paper/2502.17766/) (2025)
- [Structure-preserving Planar Simplification for Indoor Environments](https://mlsanity.com/paper/2408.06814/) (2024)
- [Hierarchical Space Partition for Surface Reconstruction](https://mlsanity.com/paper/2606.04891/) (2026)

## Abstract (arXiv)

In man-made environments such as indoor scenes, when point-based 3D reconstruction fails due to the lack of texture, lines can still be detected and used to support surfaces. We present a novel method for watertight piecewise-planar surface reconstruction from 3D line segments with visibility information. First, planes are extracted by a novel RANSAC approach for line segments that allows multiple shape support. Then, each 3D cell of a plane arrangement is labeled full or empty based on line attachment to planes, visibility and regularization. Experiments show the robustness to sparse input data, noise and outliers.