Arthur Lecert

Arthur Lecert

PhD Candidate


About me

I’m currently working as a PhD Candidate in the SIROCCO team advised by Christine GUILLEMOT and Aline ROUMY. My PhD focuses on low-light image restoration in the context of autonomous vehicles for instance. I’m also a self-taught guitar player in my free time and I practice rock climbing & bouldering.

  • Computer Vision & Signal Processing
  • Deep Learning
  • Generative modeling
  • Optimal transport
  • Computational biology
  • Mathematical physics
  • Dynamical systems
  • FOSS
  • PhD Candidate in Signal Processing & Computer Vision, 2023

    Université Rennes 1

  • MSc in Machine Learning (French degree in engineering), 2020

    ESIEE Paris

  • Exchange semester in Machine Learning, 2018

    Polytechnique Montréal

Recent Publications

(2023). Illumination colorée et information mutuelle pour le modèle Retinex en restauration d'images à faible luminosité. In GRETSI 2023 (Oral).

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(2023). GAN architecture leveraging a retinex model with colored illumination for low-light image restoration. In IEEE Access.

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(2022). A New Regularization for Retinex Decomposition of Low-Light Images. In ICIP 2022 (Oral).

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(2020). Sexing Hyalella Azteca with machine learning for bioaccumulation test. In SETAC SciCon 2.

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Work Experience

PhD Candidate
Oct 2020 – Present Rennes
  • Member of the SIROCCO team (Analysis representation, compression and communication of visual data).
  • Thesis under supervision of Christine GUILLEMOT and Aline ROUMY.
  • Developed new deep learning-based methods to restore low-light images based on the Retinex theory (correlated source separation + underdetermined problem).
  • Explored a wild range of topics (Generative modeling, GANs, diffusion and flow-based models, optimal transport and Schrödinger Bridge, Contrastive learning, Camera image processing pipeline, Classical image processing algorithms, …).
  • Used different real‐world datasets such as the Waymo dataset and satellite images provided by Airbus Defence and Space.
  • Part of a joint project with Airbus Defence and Space.
  • Reviewer for IEEE Transactions on Image Processing.
Research Intern
Jan 2020 – Jul 2020 Paris area
  • Implemented a Deep Learning model capable of sexing hyalellas reaching 99.2% accuracy.
  • Created the dataset with 2000+ pictures.
  • Internship done as part of the sustainable development lab working on ecotoxicology.
  • Applied a preprocessing on the images (mathematical morphology, pattern recognition, feature extraction, …).
  • Co‐supervision of a group of 5 undergraduate students.
  • In partnership with the Gaspard‐Monge laboratory.
Research Intern
Apr 2019 – Aug 2019 Paris area
  • Developed a platform to collect and share electricity, water and gas usage data for the creation of the new Gustave Eiffel University.
  • Applied data clustering algorithms to characterize the consumption of the different buildings.
  • Identified 4 types of electricity consumption behaviors with the intention of saving energy.
  • Conducted tests with different sensors to check the feasibility of a local low‐cost solution (Internet of things & LoRaWAN).
  • Communicated with several providers to get quotations with the aim of setting a crowd flow forecasting system (counting pedestrians and vehicles).
Research Intern
Sep 2017 – Oct 2017 Paris
  • Creation of a database for decision support and trajectory planning of an autonomous vehicle.
  • Internship done as part of the RITS team (Robotics & Intelligent Transportation Systems).