# EVOLIN Benchmark: Evaluation of Line Detection and Association

arXiv: https://arxiv.org/abs/2303.05162 · HTML: https://mlsanity.com/paper/2303.05162/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 75 references that are in the map.
- First posted on arXiv 9 Mar 2023.

## Builds on (most cited first, 25 of 25)

- [SuperGlue: Learning Feature Matching with Graph Neural Networks](https://mlsanity.com/paper/1911.11763/) (2019)
- [Learning to Find Good Correspondences](https://mlsanity.com/paper/1711.05971/) (2017)
- [Line Segment Detection Using Transformers without Edges](https://mlsanity.com/paper/2101.01909/) (2021)
- [End-to-End Wireframe Parsing](https://mlsanity.com/paper/1905.03246/) (2019)
- [Learning to Parse Wireframes in Images of Man-Made Environments](https://mlsanity.com/paper/2007.07527/) (2020)
- [Holistically-Attracted Wireframe Parsing](https://mlsanity.com/paper/2003.01663/) (2020)
- [PL-SLAM: a Stereo SLAM System through the Combination of Points and Line Segments](https://mlsanity.com/paper/1705.09479/) (2017)
- [Learning Attraction Field Representation for Robust Line Segment Detection](https://mlsanity.com/paper/1812.02122/) (2018)
- [SOLD2: Self-supervised Occlusion-aware Line Description and Detection](https://mlsanity.com/paper/2104.03362/) (2021)
- [Deep Hough-Transform Line Priors](https://mlsanity.com/paper/2007.09493/) (2020)
- [PPGNet: Learning Point-Pair Graph for Line Segment Detection](https://mlsanity.com/paper/1905.03415/) (2019)
- [TP-LSD: Tri-Points Based Line Segment Detector](https://mlsanity.com/paper/2009.05505/) (2020)
- [Fully Convolutional Line Parsing](https://mlsanity.com/paper/2104.11207/) (2021)
- [Robust Visual SLAM with Point and Line Features](https://mlsanity.com/paper/1711.08654/) (2017)
- [ELSED: Enhanced Line SEgment Drawing](https://mlsanity.com/paper/2108.03144/) (2021)
- [Structure-SLAM: Low-Drift Monocular SLAM in Indoor Environments](https://mlsanity.com/paper/2008.01963/) (2020)
- [RGB-D SLAM with Structural Regularities](https://mlsanity.com/paper/2010.07997/) (2020)
- [ManhattanSLAM: Robust Planar Tracking and Mapping Leveraging Mixture of Manhattan Frames](https://mlsanity.com/paper/2103.15068/) (2021)
- [Structure PLP-SLAM: Efficient Sparse Mapping and Localization using Point, Line and Plane for Monocular, RGB-D and Stereo Cameras](https://mlsanity.com/paper/2207.06058/) (2022)
- [PL-VINS: Real-Time Monocular Visual-Inertial SLAM with Point and Line Features](https://mlsanity.com/paper/2009.07462/) (2020)
- [Line as a Visual Sentence: Context-aware Line Descriptor for Visual Localization](https://mlsanity.com/paper/2109.04753/) (2021)
- [ULSD: Unified Line Segment Detection across Pinhole, Fisheye, and Spherical Cameras](https://mlsanity.com/paper/2011.03174/) (2020)
- [LSDNet: Trainable Modification of LSD Algorithm for Real-Time Line Segment Detection](https://mlsanity.com/paper/2209.04642/) (2022)
- [Robust Line Segments Matching via Graph Convolution Networks](https://mlsanity.com/paper/2004.04993/) (2020)
- [EVOPS Benchmark: Evaluation of Plane Segmentation from RGBD and LiDAR Data](https://mlsanity.com/paper/2204.05799/) (2022)

## Built on by (most cited first, 1 of 1)

- [A Comprehensive Review of Image Line Segment Detection and Description: Taxonomies, Comparisons, and Challenges](https://mlsanity.com/paper/2305.00264/) (2023)

## Abstract (arXiv)

Lines are interesting geometrical features commonly seen in indoor and urban environments. There is missing a complete benchmark where one can evaluate lines from a sequential stream of images in all its stages: Line detection, Line Association and Pose error. To do so, we present a complete and exhaustive benchmark for visual lines in a SLAM front-end, both for RGB and RGBD, by providing a plethora of complementary metrics. We have also labelled data from well-known SLAM datasets in order to have all in one poses and accurately annotated lines. In particular, we have evaluated 17 line detection algorithms, 5 line associations methods and the resultant pose error for aligning a pair of frames with several combinations of detector-association. We have packaged all methods and evaluations metrics and made them publicly available on web-page https://prime-slam.github.io/evolin/.