Host Institution: University Paris-Est Créteil, LISSI laboratoryIndustry Partner: Declic Startup – an innovative social networking and event organization platform Supervision: Dr. Alice Othmani, HDR, Professor at University Paris-Est Créteil (UPEC)Duration: 3 yearsLocation: Paris, France with potential collaborations in the Middle East and Europe 🔍 Context and Motivation The rapid growth…
Titre de la thèse : Optimisation multi-objectifs de l’acquisition et de la modélisation de l’apparence des surfaces complexes par approches d’IA
Deep neural networks are currently one of the most successful models in image processing and computer vision [1-4, 10-13]. Their principle consists in learning convolutional filters, together with attention [14,15] and fully connected layers, that maximize classification and generation performances. Large generative models (LGMs) [5] are a particular category of…
Socio-economic and scientific context An intracranial aneurysm (IA) is a deformation of the cerebral artery wall, leading to a fragile arterial zone that may rupture. Aneurysmal rupture most often causes a subarachnoid hemorrhage (SAH), which has a poor prognosis. It is estimated that one-third of patients with this condition will…
Un sujet de thèse est ouvert dans le cadre du projet ANR PERSAPLAN « Arthroplastie Personnalisée de l’Epaule Inversée : intégration des caractéristiques fonctionnelles et biomécaniques du patient dans le Planning chirurgical » (ANR-24-CE45-7139-01). Contexte: Le projet de thèse Perceus a pour objectif d’améliorer les résultats post-opératoires de l’arthroplastie d’épaule…
Socio-economic and scientific context Low Grade Gliomas (LGG, WHO grade II) are infiltrative brain tumours that usually occur in young patients (mean age of 38 years). Due to their slow growth and brain plasticity, most patients provide normal or nearly normal clinical examination for several years. Surgery is considered to…
General information Description Context Landmark detection, description and matching is the cornerstone of autonomous visual localization systems deployed in unknown environments. While most widely-adopted and accurate solutions exploit low-level landmarks such as points or lines, dealing with large-scale and/or visually ambiguous environments remains highly challenging due to the inherent multiplicity,…
Keywords : vision foundation models, physics-grounding, computer vision, scene understanding Supervisors : Raoul de Charette (Inria, Paris) and Tuan-Hung Vu (Inria / Valeo.ai, Paris) Description: The objective of the PhD is to improve the explicit understanding of physics in Vision Foundation Models (VFM). While the latter are typically trained on reconstruction…
