Computer Graphics Laboratory

Slides

• Lecture 0: Introduction
• Lecture 1: Robust Fitting and Optimization
• Lecture 2: Global Optimization I
• Lecture 3: Global Optimization II
• Lecture 4: Dimensionality Reduction
• Lecture 5: Markov Random Fields and Graph-cuts
• Lecture 6: Space Transformations
• Lecture 7: Optimal Transport
• Lecture 8: Variational Methods I
• Lecture 9: Variational Methods II
• Lecture 10: Deep Learning I
• Lecture 11: Deep Learning II - GANs
• Lecture 12: Deep Learning III
• Exam Details

Important: The course notes are only accessible from ETH IP range. These slides were generated as course documentation only. They contain images with unknown copyright. Therefore, the slides are provided exclusively for students attending the course to study the course material. Please do not copy or distribute these documents.