Welcome to the Visual Learning Lab Heidelberg

The Visual Learning Lab Heidelberg works at the intersection of Computer Vision and Machine Learning. This means that we take images, videos or other dense measurements and process them, or extract useful information hidden in the data. We work on a broad range of applications, such as segmentation, pose estimation, matching, tracking, detection, and scene understanding. We are interested in talking to researchers from other disciplines, such as computational biology, medicine, astronomy, or environmental physics, and see if we can contribute with our knowledge. On the methodological side we focus on deep learning, explainable machine learning, scalable optimization of graphical models, as well as training data simulation.

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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

Machine Learning

focusing on Explainable Machine Learning and Deep Learning

Combinatorial Optimization

focusing on Graphical Models, Diversity, and Large-Scale Optimization

Scene Understanding

focusing on 6D Pose estimation, Dense Matching, and Instance Recognition

Natural Science

focusing on BioImaging, Medicine and related fields

Training Data Generation

focusing on Mixed Realty, Ground Truth Capture and Lightfields

Collaborators & Industrial Partners

Over the last years we have been collaborating with various scientific partners – such as MPI Tübingen, Oxford University, University College London, Imperial College London, ETH Zürich, Skoltech Moscow, Stanford University, TU Darmstadt, Prague University, University of Hannover, IST Vienna, TU Vienna, MPI Saarbrücken, TU Dresden, MPI-CBG and CSBD Dresden, and more.
We have also been collaborating with various industrial research labs - such as Microsoft Research Cambridge, Bejing and Redmond, Daimler, and Facebook Artificial Intelligence Researchers (FAIR).
We are part of the Heidelberg HCI 3rd phase, where we collaborate closely with Bosch.

Prof. Dr. Carsten Rother

Head of VLL.
Please arrange an appointment via Jiannis Giatagantzidis (Secretariat).

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Carsten Rother is mentoring the start-up Rabbit AI. Find out more ...

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