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PA - C8 - INF631 : Analysis and Deep Learning on Geometric Data

Domaine > Informatique.


Objectives :


This course will introduce students to advanced topics in modern geometric 3D data analysis with focus on a) mathematical foundations (discrete differential geometry, mapping, optimization), and b) deep learning for best performing methods. We will give an overview of the foundations in 3D shape analysis and processing before moving to modern techniques based on deep learning for solving problems such as shape classification, correspondence, parametrization, etc.

Content :


The course is divided into four lectures and four lab sessions. The topics covered include:

  • Intro to 3D Shape Representaiton and Discrete Differential Geometry,

  • Optimization of geometric energies,

  • Deep learning on curved surfaces,

  • Analysis and machine learning on point clouds

Language :

The course will be taught in English by Maks Ovsjanikov and Etienne Corman.


Evaluation :

Oral paper presentation.

Format des notes

Numérique sur 20

Littérale/grade réduit

Pour les étudiants du diplôme M2 IGD - Interaction, Graphic and Design

Pour les étudiants du diplôme M2 Data AI - Data and Artificial Intelligence

Pour les étudiants du diplôme MScT-Artificial Intelligence and Advanced Visual Computing

Le rattrapage est autorisé (Note de rattrapage conservée)
    L'UE est acquise si note finale transposée >= C
    • Crédits ECTS acquis : 2 ECTS

    La note obtenue rentre dans le calcul de votre GPA.

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