Research Topics

Associated with Inria Saclay, the Centre de Vision Numérique, created in 2011, is at the intersection between mathematics and computer science. It is in search of mathematical models and their IT solutions for automatic structuring, interpreting and understanding big (visual) data with a focus on machine learning, computer vision and discrete models in biomedical image analysis.

Computer Vision

Image reconstruction, border detection, segmentation with or without modeling, flow estimation and monitoring, image analysis, object recognition and large-scale 3D modeling based on a grammar

Machine Learning and Optimization

Self-learning, probabilistic graphical models, multiple instance learning, structured output regression, kernel methods, and multitask, online, or transfer learning, etc.

Biomedical Image Analysis (GALEN-Inria team)

Compressed reconstruction and detection, tumor detection, organ segmentation, image registration and deformable fusion, longitudinal modeling of organs, virtual anatomy, population studies and understanding of the brain, etc.

The Center of Visual Computing of CentraleSupelec & Inria, Saclay, Ile-de-France, organized a summer school in Biomedical Image Analysis: Modalities, Methodologies & Clinical Research at the Institut Henri Poincaré at the heart of Paris. This was an official event of the Medical Image Computing and Computer Assisted Intervention Society (MICCAI). Please find out all the lectures given for this special event.

Fields of Application

  • Complex industrial systems (automation, optical sorting, robotics, control systems, non-destructive testing)

  • Automotive Industry (assisted driving, pedestrian detection, cruise control, parking assistance)

  • Health (computer-aided diagnostics, multimodal sensors, data mining, biomarker imaging, computer-aided surgery) 

 

Key Figures

  • Instructor-researchers and researchers: 5
  • PhD students: 17
  • Technical and administrative staff: 3
  • Interns: 8
  • Patents: 1
  • Publications: 22

 

Academic Partners

Inria (France), École des Ponts ParisTech (France), Henri Mondor University Hospital (France), Georges Pompidou European Hospital (France), Pitié-Salpêtrière Hospital (France), Montpelier University Hospital (France), CentraleSupélec (France), Stanford University (USA), StonyBrook University (USA), University of Pennsylvania (USA), UCLA (USA), Technical University of Munich (Germany), University of Lugano (Switzerland), University of Oxford (UK), University College London (UK), University of Oulu (Finland), École Polytechnique de Montréal (Canada), International Institute of Information Technology, Hyderabad (India)

 

Business and Research Clusters

Digiteo, Medicen, Cap Digital

 

Industrial Partners

GE Healthcare, Siemens Medical Solutions, Intrasense, LLTech
 

Contact

 

Website: http://cvn.ecp.fr/

Director: Jean-Christophe PESQUET
Tel.: +33 (0)1 41 13 17 85
Fax: +33 (0)1 41 13 10 06

Email: Jean-Christophe.pesquet@centralesupelec.fr 

 

Latest submissions

Article in a review
06/01/2025
Robust automatic crater detection at all latitudes on Mars with Deep-learning
Martinez Leonard, François Andrieu, Frédéric Schmidt, Hugues Talbot, Bentley Mark
Communication on a congress
04/06/2025
Pre-submission / Working document
02/11/2025
Training Deep Learning Models with Norm-Constrained LMOs
Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos, Zhenyu Zhu, Antonio Silveti-Falls, Volkan Cevher
Pre-submission / Working document
01/14/2025
Article in a review
01/02/2025
Performance analysis of a deep-learning algorithm to detect the presence of inflammation in MRI of sacroiliac joints in patients with axial spondyloarthritis
Joeri Nicolaes, Evi Tselenti, Theodore Aouad, Clementina López-Medina, Antoine Feydy, Hugues Talbot, Bengt Hoepken, Natasha de Peyrecave, Maxime Dougados
Browse all laboratory submissions on HAL