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Computer Vision

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Welcome to the Computer Vision Lab Dresden    

Computer Vision is a science that develops models and methods for understanding, analysing, acquiring and processing images and in generally high-dimensional “visual” data. Computer Vision is an inter-disciplinary field with strong links to Machine Learning, Optimization, Biology, Computer Graphics, and Human Computer Interaction. The mission of the Computer Vision Lab Dresden is to develop novel theoretical concepts which are practically relevant. We work on a broad set of applications, ranging from physics-based vision to semantic scene understanding, and BioImaging. On the theoretical side we focus on efficient optimization and learning techniques for graphical models.


News

  • We have two papers accepted to CVPR '14, on large displacement RGBD flow and semantic segmentation, in collaboration with Phil Torr's team at Oxford University.
  • We have openings for PostDocs, PhD Students, and Interns, and SHKs (please see job offers )
  • We have a NIPS‘13 paper on joint object recognition and intrinsic image estimation. This is joint work with Vibhav Vineet, and Phil Torr from Oxford University.
  • We have new topics for Diplom, Master, Bachelor,Grosser Beleg ( click here )
  • Best Paper Award at CVPR 13 on Discriminative Non-Blind Deconvolution, Uwe Schmidt, Carsten Rother, Sebastian Nowozin, Jeremy Jancsary, and Stefan Roth.

Office Hours

Katrin Heber (secretary): Monday, Tuesday, Wednesday, and Friday: 14-16
Carsten Rother: please arrange an appointment with Katrin Heber


Collaborators

We have strong, international collaborations: Oxford University, University College London, HCI Heidelberg, TU Darmstadt, Microsoft Research Cambridge, Prague University, TU Vienna, Adobe, TU Munich, MPI Tuebingen, and more.

Last modified: 25th Feb 2014, 5.46 PM
Author: Bettina Weser

Contact

Prof. Ph.D.
Carsten Rother

Room INF-2022
Phone: +49 351 463-38379

Secretary:
Katrin Heber
Nöthnitzer Str. 46
01187 Dresden

Room INF-2023
Phone: +49 351 463-38372
Fax: +49 351 463-32369

(*All TU Dresden emails are to be completed by '@tu-dresden.de'.)