Vincent Gaudillière

Vincent Gaudillière

Computer Vision Researcher

SnT, University of Luxembourg

About me

I am Research Associate at SnT, Interdisciplinary Center for Security, Reliability and Trust, University of Luxembourg. My research interests include visual localization, pose estimation and geometric deep learning. I carried out my PhD Thesis at the French National Institute for Research in Digital Science and Technology (Inria). I am currently member of the Computer Vision, Imaging and Machine Intelligence Research Group (CVI2), in which part of my work is dedicated to space applications.

News

Reviewing responsibilities

Computer vision conferences (CVPR, ICCV, ECCV, WACV, 3DV) and journals (CVIU, TVCG), robotics conferences (IROS, ICRA) and journals (RA-L), image processing conference (ICIP).

Education
  • PhD in Computer Science, 2020

    Inria, France

  • MEng in Signal & Image Processing, Communication Systems, Multimedia, 2016

    Grenoble Institute of Technology, France

  • Exchange Semester, 2016

    EPFL, Switzerland

Experience

 
 
 
 
 
SnT, University of Luxembourg
Research Associate
February 2021 – Present Luxembourg, Luxembourg
Computer Vision for Space Applications
 
 
 
 
 
Inria
Transfer & Innovation Engineer
January 2020 – December 2020 Nancy, France
Object-based Localization
 
 
 
 
 
Inria
PhD Thesis
December 2016 – December 2019 Nancy, France
Visual Localization in a World of Objects
 
 
 
 
 
PIX4D
Master Thesis / Work placement
February 2016 – July 2016 Lausanne, Switzerland
GPU-Accelerated Large Scale Surface Reconstruction

Other Publications

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(2023). Space Debris: Are Deep Learning-based Image Enhancements part of the Solution?. ISCS 2023.

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(2023). Self-Supervised Learning for Place Representation Generalization across Appearance Changes.

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(2022). Shot-processing device. US Patent App. 17/614,111.

PDF

(2022). Image Enhancement for Space Surveillance and Tracking. IAC 2022.

ORbiLu

(2022). Pose Estimation of a Known Texture-Less Space Target using Convolutional Neural Networks. IAC 2022.

PDF ORbiLu