Visual Localization via Few-Shot Scene Region Classification

Siyan Dong, Shuzhe Wang, Yixin Zhuang, Juho Kannala, Marc Pollefeys, Baoquan Chen

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

4 Citations (Scopus)


Visual (re)localization addresses the problem of estimating the 6-DoF (Degree of Freedom) camera pose of a query image captured in a known scene, which is a key building block of many computer vision and robotics applications. Recent advances in structure-based localization solve this problem by memorizing the mapping from image pixels to scene coordinates with neural networks to build 2D-3D correspondences for camera pose optimization. However, such memorization requires training by amounts of posed images in each scene, which is heavy and inefficient. On the contrary, few-shot images are usually sufficient to cover the main regions of a scene for a human operator to perform visual localization. In this paper, we propose a scene region classification approach to achieve fast and effective scene memorization with few-shot images. Our insight is leveraging a) pre-learned feature extractor, b) scene region classifier, and c) meta-learning strategy to accelerate training while mitigating overfitting. We evaluate our method on both indoor and outdoor benchmarks. The experiments validate the effectiveness of our method in the few-shot setting, and the training time is significantly reduced to only a few minutes. 11Code available at:

Original languageEnglish
Title of host publicationProceedings - 2022 International Conference on 3D Vision, 3DV 2022
Number of pages10
ISBN (Electronic)978-1-6654-5670-8
Publication statusPublished - Feb 2023
MoE publication typeA3 Book section, Chapters in research books
EventInternational Conference on 3D Vision - Prague, Czech Republic
Duration: 12 Sept 202216 Sept 2022

Publication series

NameInternational Conference on 3D Vision proceedings
ISSN (Electronic)2475-7888


ConferenceInternational Conference on 3D Vision
Abbreviated title3DV
Country/TerritoryCzech Republic


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