# Single-Shot Global Localization via Graph-Theoretic Correspondence Matching

Source: [Single-Shot Global Localization via Graph-Theoretic Correspondence Matching](<https://www.sota2.com/research/paper/68fa6fa31e209131cea46da5>)

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

Data updated: 2025-10-27T06:23:26.146Z

Authors: Shigemichi Matsuzaki, Kenji Koide, Shuji Oishi, Masashi Yokozuka, Atsuhiko Banno

Published: 2023-06-06T12:52:07.000Z

## Abstract

This paper describes a method of global localization based on graph-theoretic association of instances between a query and the prior map. The proposed framework employs correspondence matching based on the maximum clique problem (MCP). The framework is potentially applicable to other map and/or query modalities thanks to the graph-based abstraction of the problem, while many of existing global localization methods rely on a query and the dataset in the same modality. We implement it with a semantically labeled 3D point cloud map, and a semantic segmentation image as a query. Leveraging the graph-theoretic framework, the proposed method realizes global localization exploiting only the map and the query. The method shows promising results on multiple large-scale simulated maps of urban scenes.

## 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/2306.03641>)

[PDF](<https://arxiv.org/pdf/2306.03641.pdf>)