Search Results for author: Pauline Trouvé-Peloux

Found 7 papers, 2 papers with code

Pix2Point: Learning Outdoor 3D Using Sparse Point Clouds and Optimal Transport

no code implementations30 Jul 2021 Rémy Leroy, Pauline Trouvé-Peloux, Frédéric Champagnat, Bertrand Le Saux, Marcela Carvalho

The 3D information was usually obtained from images by stereo-photogrammetry, but deep learning has recently provided us with excellent results for monocular depth estimation.

Monocular Depth Estimation

Multi-Task Learning of Height and Semantics from Aerial Images

1 code implementation18 Nov 2019 Marcela Carvalho, Bertrand Le Saux, Pauline Trouvé-Peloux, Frédéric Champagnat, Andrés Almansa

Aerial or satellite imagery is a great source for land surface analysis, which might yield land use maps or elevation models.

Multi-Task Learning

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

no code implementations4 Nov 2019 Marcela Carvalho, Maxime Ferrera, Alexandre Boulch, Julien Moras, Bertrand Le Saux, Pauline Trouvé-Peloux

This paper is a technical report about our submission for the ECCV 2018 3DRMS Workshop Challenge on Semantic 3D Reconstruction \cite{Tylecek2018rms}.

3D Reconstruction Autonomous Navigation +2

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

no code implementations31 Oct 2019 Maxime Ferrera, Vincent Creuze, Julien Moras, Pauline Trouvé-Peloux

The data acquisition is performed using Remotely Operated Vehicles equipped with a monocular monochromatic camera, a low-cost inertial measurement unit, a pressure sensor and a computing unit, all embedded in a single enclosure.

Simultaneous Localization and Mapping

The Aqualoc Dataset: Towards Real-Time Underwater Localization from a Visual-Inertial-Pressure Acquisition System

no code implementations19 Sep 2018 Maxime Ferrera, Julien Moras, Pauline Trouvé-Peloux, Vincent Creuze, Denis Dégez

This paper presents a new underwater dataset acquired from a visual-inertial-pressure acquisition system and meant to be used to benchmark visual odometry, visual SLAM and multi-sensors SLAM solutions.

Visual Odometry

Real-time Monocular Visual Odometry for Turbid and Dynamic Underwater Environments

no code implementations15 Jun 2018 Maxime Ferrera, Julien Moras, Pauline Trouvé-Peloux, Vincent Creuze

In the context of robotic underwater operations, the visual degradations induced by the medium properties make difficult the exclusive use of cameras for localization purpose.

Monocular Visual Odometry Optical Flow Estimation

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