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20182024
most citedAQUALOC: An Underwater Dataset for Visual-Inertial-Pressure Localization

122 citations · 123 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CV2024

From 2D to 3D: AISG-SLA Visual Localization Challenge

Jialin Gao, Bill Ong, Darld Lwi +13

Research in 3D mapping is crucial for smart city applications, yet the cost of acquiring 3D data often hinders progress. Visual localization, particularly monocular camera position…

cs.CV202318 cited

Eiffel Tower: A Deep-Sea Underwater Dataset for Long-Term Visual Localization

Clémentin Boittiaux, Claire Dune, Maxime Ferrera +5

Visual localization plays an important role in the positioning and navigation of robotics systems within previously visited environments. When visits occur over long periods of tim…

cs.CV2021

Hyperspectral 3D Mapping of Underwater Environments

Maxime Ferrera, Aurélien Arnaubec, Klemen Istenic +2

Hyperspectral imaging has been increasingly used for underwater survey applications over the past years. As many hyperspectral cameras work as push-broom scanners, their use is usu…

cs.CV2021

OVSLAM : A Fully Online and Versatile Visual SLAM for Real-Time Applications

Maxime Ferrera, Alexandre Eudes, Julien Moras +2

Many applications of Visual SLAM, such as augmented reality, virtual reality, robotics or autonomous driving, require versatile, robust and precise solutions, most often with real-…

cs.CV20191 cited

Technical Report: Co-learning of geometry and semantics for online 3D mapping

Marcela Carvalho, Maxime Ferrera, Alexandre Boulch +3

This paper is a technical report about our submission for the ECCV 2018 3DRMS Workshop Challenge on Semantic 3D Reconstruction \cite{Tylecek2018rms}. In this paper, we address 3D s…

cs.CV2019122 cited

AQUALOC: An Underwater Dataset for Visual-Inertial-Pressure Localization

Maxime Ferrera, Vincent Creuze, Julien Moras +1

We present a new dataset, dedicated to the development of simultaneous localization and mapping methods for underwater vehicles navigating close to the seabed. The data sequences c…