Computer Graphics Laboratory

Slides

• Lesson 1: Introduction - Representation, Sampling, Reconstruction I
• Lesson 2: Representation, Sampling, Reconstruction II
• Lesson 3: Robust Optimization
• Lesson 4: Global Optimization
• Lesson 5: Dimension Reduction
• Lesson 6: Labelling and Belief Propagation
• Lesson 7: Space Transformations
• Lesson 8: Sampling and Anti-aliasing
• Lesson 9: Practical Numerical Methods
• Lesson 10: Structure Learning and Spectral Methods I
• Lesson 11: Structure Learning and Spectral Methods II

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.