HSCNet++: Hierarchical Scene Coordinate Classification and Regression for Visual Localization with Transformer

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00372774" target="_blank" >RIV/68407700:21230/24:00372774 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s11263-023-01982-9" target="_blank" >https://doi.org/10.1007/s11263-023-01982-9</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11263-023-01982-9" target="_blank" >10.1007/s11263-023-01982-9</a>

Result language
angličtina
Original language name
HSCNet++: Hierarchical Scene Coordinate Classification and Regression for Visual Localization with Transformer
Original language description
Visual localization is critical to many applications in computer vision and robotics. To address single-image RGB localization, state-of-the-art feature-based methods match local descriptors between a query image and a pre-built 3D model. Recently, deep neural networks have been exploited to regress the mapping between raw pixels and 3D coordinates in the scene, and thus the matching is implicitly performed by the forward pass through the network. However, in a large and ambiguous environment, learning such a regression task directly can be difficult for a single network. In this work, we present a new hierarchical scene coordinate network to predict pixel scene coordinates in a coarse-to-fine manner from a single RGB image. The proposed method, which is an extension of HSCNet, allows us to train compact models which scale robustly to large environments. It sets a new state-of-the-art for single-image localization on the 7-Scenes, 12-Scenes, Cambridge Landmarks datasets, and the combined indoor scenes.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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