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.
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
The course will be taught in English by Maks Ovsjanikov and Etienne Corman.
Oral paper presentation.
- M2 Data AI - Data and Artificial Intelligence
- MScT-Artificial Intelligence and Advanced Visual Computing
Parcours de rattachement
Format des notesNumérique sur 20Littérale/grade réduit
Pour les étudiants du diplôme MScT-Artificial Intelligence and Advanced Visual ComputingLe rattrapage est autorisé (Note de rattrapage conservée)
- Crédits ECTS acquis : 2 ECTS
La note obtenue rentre dans le calcul de votre GPA.