Interacted Planes Reveal 3D Line Mapping

TL;DR

LiP-Map introduces a novel joint optimization framework for 3D line mapping that explicitly models line and planar primitives, achieving high accuracy and efficiency in structured scene reconstruction and visual localization.

Contribution

The paper presents LiP-Map, a new method that integrates planar topology into 3D line mapping through explicit line-plane interactions, improving reconstruction quality and efficiency.

Findings

LiP-Map outperforms state-of-the-art methods on multiple datasets.

Reconstruction typically completes in 3 to 5 minutes per scene.

LiP-Map enhances line-assisted visual localization performance.

Abstract

3D line mapping from multi-view RGB images provides a compact and structured visual representation of scenes. We study the problem from a physical and topological perspective: a 3D line most naturally emerges as the edge of a finite 3D planar patch. We present LiP-Map, a line-plane joint optimization framework that explicitly models learnable line and planar primitives. This coupling enables accurate and detailed 3D line mapping while maintaining strong efficiency (typically completing a reconstruction in 3 to 5 minutes per scene). LiP-Map pioneers the integration of planar topology into 3D line mapping, not by imposing pairwise coplanarity constraints but by explicitly constructing interactions between plane and line primitives, thus offering a principled route toward structured reconstruction in man-made environments. On more than 100 scenes from ScanNetV2, ScanNet++, Hypersim, 7Scenes, and Tanks\&Temple, LiP-Map improves both accuracy and completeness over state-of-the-art methods. Beyond line mapping quality, LiP-Map significantly advances line-assisted visual localization, establishing strong performance on 7Scenes. Our code is released at https://github.com/calmke/LiPMAP for reproducible research.