Advisor(s):
Peter Vincent Gehler
My current research is focused on building robust computer vision and machine learning systems based on deep probabilistic models that allow failure prediction and uncertainty quantification.
probabilistic models machine learning uncertainty quantification deep learning robust vision
An expressive model of human motion is essential for action classification, motion prediction and synthesis. To that end, we are exploring several deep network architectures to predict human movement.
Current methods for motion prediction typically do not wo...
Julieta Martinez Judith Bütepage Javier Romero Hedvig Kjellström Michael Black Ludovic Righetti Partha Ghosh Sergey Prokudin
Prokudin, S., Gehler, P., Nowozin, S.
European Conference on Computer Vision (ECCV), September 2018 (conference)
Prokudin, S., Kappler, D., Nowozin, S., Gehler, P.
In Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland, September 12–15, 2017, Proceedings, pages: 52-62, Springer International Publishing, Cham, 2017 (inbook)