Fakultät Informatik

Deep Learning and Numerical Simulations for Visual Effects

 

Deep Learning and Numerical Simulations for Visual Effects (IN 2298)

Time, Place:

Wednesday , 16:00,  HS2

Thursday, 10:00,  HS2

First lecture: Thu., Apr. 27.,2017

Prerequisites:

Computer Graphics and Game Physics highly recommended

Materials:

moodle page

Exam:

tba

+

Content

This course targets machine learning techniques and numerical simulation
algorithms for materials such as fluids and deformable objects in the context
of computer animation. The lecture and exercises will all be in English. The following topics are discussed:

  • Convolutional neural networks & deep learning techniques
  • Physically-based animation, fluid modeling
  • Discretizations, and partial differential equations
  • Exercises to gain hands-on experience with CNN training and fluid simulation algorithms

Prerequisites

Computer Gaphics Fundamentals, and Game Physics (Lagrangian simulation techniques)

Literature

 

Machine Learning

Computational Fluid Dynamics

Elasticity

  • William S. Slaughter, The linearized theory of elasticity, Birkhaeuser, 2002

Computer Animation

  • Parent: Computer Animation: Algorithms and Techniques, Morgan Kaufmann

 

 

Lecture Slides

Will be made available on the moodle page

 

News

Matthias Niessner, our new Professor from Stanford University, offers a number of interesting topics for  master theses.

 

A new PhD/PostDoc position on  Computational Fabrication and 3D Printing is available at the Computer Graphics & Visualization group.

 

A new PhD position is available at the games engineering group.  Check it out here.