Learning Local Regularization for Variational Image Restoration
Jean Prost, Antoine Houdard, Andrés Almansa, Nicolas Papadakis
CV
Education
- B.S. in GitHub, GitHub University, 2012
- M.S. in Jekyll, GitHub University, 2014
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
Work experience
- Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
- Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
SCOTCH and SODA: A Transformer Video Shadow Detection Framework
Lihao Liu, Jean Prost, Lei Zhu, Nicolas Papadakis, Pietro Lio, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero
Inverse problem regularization with hierarchical variational autoencoders
Jean Prost, Antoine Houdard, Nicolas Papadakis, Andrés Almansa
Plug-and-Play image restoration with Stochastic deNOising REgularization
Marien Renaud, Jean Prost, Arthur Leclaire, Nicolas Papadakis
Efficient posterior sampling for diverse super-resolution with hierarchical VAE Prior
Jean Prost, Antoine Houdard, Nicolas Papadakis, Andrés Almansa
Talks
Apprentissage d’une fonction de régularisation locale pour la restauration d’images”
Talk at ORASIS 2021, Saint-Ferréol
Learning local regularization for variational image restoration
Mini-symposium at SIAM Conference on Imaging Science (IS22), Virtual conference
Diverse image super-resolution with hierarchical variational autoencoders
Poster at 3rd IMA Conference on Inverse Problems from Theory to Application, ICMS, Bayes Centre, Edinburgh
Diverse image super-resolution with hierarchical variational autoencoders
Talk at Generative models: Control and (mis)Usage, CNRS Ile-de-France Villejuif
Diverse image super-resolution with hierarchical variational autoencoders
Talk at Cambridge Image Analysis seminar, Cambridge
Diverse image super-resolution with hierarchical variational autoencoders
Talk at Mathematical Models for Plug-and-play Image Restoration, Paris
Teaching
Service and leadership
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