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Computer Vision

Welcome to the Computer Vision Group of the University of Siegen (previously known as the Visual Scene Analysis Group). The group is headed by Prof. Michael Möller. On this website, you can find information about the group members, our courses, publications, final thesis, and open positions.




The Computer Vision Group conducts research in the field of mathematical image processing, computer vision, and machine learning with a special focus on ways to combine machine learning and energy minimization methods. In this context we are interested in provable deep learning as well as optimization techniques such as convex relaxations or functional lifting, and work on (nonlinear) multiscale methods. Please visit our publications page to find out more about our recent research. 


Our paper "Improving Deep Learning for HAR with shallow LSTMs" won the Best Paper Award at ISWC 2021!

Dr. Yuval Bahat (https://sites.google.com/view/yuval-bahat/home) has joined the University of Siegen via the cofund STAR project in a collaboration with Princeton University (Group of Felix Heide, https://light.princeton.edu/). 

Women in Vision Siegen

Two female PhD and one master student at the Computer Vision group started an initiative to encourage more women to study computer science in general and computer vision in particular. They have created a website as a plattform and are regularly inviting female researchers to give talks! Please check out https://sites.google.com/view/women-in-vision-siegen and feel free to get in touch - even just for having a coffee, forming a female student and researcher network, or learning more about what life (and research) as a PhD student is like!

Bachelor or Master Thesis

To handle the large number requests for student projects, future Bachelor and Master Thesis as well as Studienarbeiten will be supervised by PhD students with feedback to Prof. Möller in larger time periods. The table below shows our current group members, their availability to supervise theses, and the topics/areas they offer theses in. In case you are interested, please contact the respective PhD student directly and include a transcript of your studies. Note that prior knowledge in our fields of research (e.g. gained by attending the chair's lectures) is a requirement to be able to write a final thesis with us. We do not offer internships. If you study computer science and would like to form a project group (Projektgruppe) in the field of machine learning and/or computer vision, please contact Michael Möller at michael.moeller(at)uni-siegen.de.


PhD Available Slots Topic / Area Email
Hartmut Bauermeister Fully occupied Optimization algorithms and model-informed machine learning hartmut.bauermeister(at)uni-siegen.de
Vaishnavi Gandikota Fully occupied Generative models and deep learning applications in image reconstruction kanchana.gandikota(at)uni-siegen.de
Hannah Dröge Fully occupied Image and video segmentation, hybrid model- and learning-based approaches hannah.droege(at)uni-siegen.de
Marcel Seelbach  1 slot free Optimization methods using quantum computing marcel.seelbach(at)uni-siegen.de
Dr. Zorah Lähner  Fully occupied 3D Shape Analysis and Geometric Deep Learning See topics here

Marius Bock

Fully occupied Deep Learning in Human Activity Recognition marius.bock(at)uni-siegen.de