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Variational Methods for Computer Vision

Tutorial ICCV 2011

Daniel Cremers, Bastian Goldlücke, Thomas Pock

Content

  • Basic concepts of variational methods: variational approach, Euler-Lagrange equations, duality, …
  • Foundations of convex optimization and convex relaxation techniques
  • Optimal first-order algorithms for convex optimization
  • Variational formulations for classical computer vision problems: image segmentation, optical flow, stereo and multiview reconstruction, …
  • Relations to discrete optimization and Markov random fields
  • Mumford-Shah and multilabel problems
  • Numerical implementation and GPU acceleration

Schedule & Slides

Sunday, Nov. 6, Full day

9:30 - 10:15Mathematical FoundationsBastian Goldlücke
Coffee break
10:35 - 11:20Continuous Optimization in Computer VisionThomas Pock
Coffee break
11:40 - 12:25Variational Methods and Geometric ReconstructionDaniel Cremers
Lunch break
14:00 - 14:45Convex Relaxation for Motion and StereoThomas Pock
Coffee break
15:05 - 15:50Convex Relaxations for Multi-label ProblemsDaniel Cremers
Coffee break
16:10 - 16:55Vectorial Multilabel ProblemsBastian Goldlücke

Complete Slide Download

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Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

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News

03.04.2022

In April 2022 Jürgen Sturm, Christian Kerl and Daniel Cremers were featured among the top 10 most influential scholars in robotics of the last decade.

31.03.2022

We have open PhD and postdoc positions! To apply, please use our application form.

08.03.2022

We have six papers accepted to CVPR 2022 in New Orleans!

31.01.2022

We have two papers accepted to ICRA 2022 - congrats to Lukas von Stumberg, Qing Cheng and Niclas Zeller!

05.12.2021
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