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Apprentissage de modalités auxiliaires pour la localisation basée vision

Abstract : In this paper we present a new training with side modality framework to enhance image-based localization. In order to learn side modality information, we train a fully convo-lutional decoder network that transfers meaningful information from one modality to another. We validate our approach on a challenging urban dataset. Experiments show that our system is able to enhance a purely image-based system by properly learning appearance of a side modality. Compared to state-of-the-art methods, the proposed network is lighter and faster to train, while producing comparable results.
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https://hal.archives-ouvertes.fr/hal-01928002
Contributor : Nathan Piasco <>
Submitted on : Tuesday, November 20, 2018 - 11:40:16 AM
Last modification on : Tuesday, May 12, 2020 - 8:28:22 AM

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  • HAL Id : hal-01928002, version 1

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Nathan Piasco, Désiré Sidibé, Valérie Gouet-Brunet, Cédric Demonceaux. Apprentissage de modalités auxiliaires pour la localisation basée vision. Reconnaissance des Formes, Image, Apprentissage et Perception (RFIAP), Jun 2018, Marne-la-Vallée, France. ⟨hal-01928002⟩

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