Welcome to the Computer Vision Lab Dresden


Computer Vision is a science that develops models and methods for understanding, analyzing, acquiring and processing images and generally high-dimensional structured 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 range of application areas, from image matching, via semantic scene understanding, to Bio Imaging. On the theoretical side we focus on optimization and learning in probabilistic graphical models, as well as Deep Learning.
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Latest News

  • Stephan Ihrke wins the Carl Zeiss Diplompreis

    Stephan Ihrke wins the Carl Zeiss Diplompreis

    Stephan Ihrke wins the Carl Zeiss Diplompreis for his Diploma thesis: “Casting Light on Object Pose Estimation via Object Coordinate …
  • MICCAI 2015 Ear Data Set

    MICCAI 2015 Ear Data Set

    The MICCAI 2015 ear data set used in our paper “Semantic 3-D Labeling of ear implants using a global parametric …
  • MSF Workshop at ICCV 2015

    MSF Workshop at ICCV 2015

    CVLD organizes together with Rama Chellappa, Christian Heipke, Alper Yilmaz, Clément Mallet, Yury Vizilter the 3rd ICCV2015 Workshop: Multi-Sensor Fusion for Dynamic Scene Understanding (MSF 2015), which …
  • 3 papers accepted to ICCV 2015

    3 papers accepted to ICCV 2015

    (1) Learning to compare a synthetic rendered image with a real observation Image for better 6D Object Pose estimation (2) …
  • 6D Object Pose  Workshop at ICCV2015

    6D Object Pose Workshop at ICCV2015

    We are helping to organize the 1st International Workshop on Recovering 6D Object Pose In conjuction with ICCV 2015, Santiago. …

RESEARCH HIGHLIGHTS 


The Rich Scene Model (ERC Consolidator Grant)

Given a sequence of images the goal is to recover a rich, detailed representation of the 3D world, ranging from physical to semantical aspects. To achieve this we investigate new ways to combine feature learning, modelling, physical laws, and optimization in large-scale discrete-continuous-valued probabilistic graphical model. 

Our Research


Optimization & Learning

with a focus on graphical models, deep models, and large-scale optimization.

Image Matching

with a focus on 3-9DoF scene flow, as well as jointly recovering multiple physical aspects.

Scene Understanding

with a focus on 3D semantic scene under-standing, and model-based vision.

Bio Imaging

with a focus on segmentation, tracking, and matching – jointly with teams from MPI-CBG.

Image Analysis

with a focus on segmentation, interactive techniques, as well as camera design.




Regular Events


Collaborators & Industrial Partners

We have strong international collaborations with Oxford University, University College London, Skoltech Moscow, Stanford University, HCI Heidelberg, TU Darmstadt, Microsoft Research Cambridge, Prague University and others.
We also have industrial collaborations with Daimler Research, Adobe (Seattle) and Basler AG.


Office Hours

Katrin Heber

Secretary
Monday, Tuesday, Wednesday, Friday
14:00 - 16:00

Prof. PhD. Carsten Rother

Head of CVLD.
Please arrange an appointment with Katrin Heber (Secretary).