4 citations · 4 across the 5 of their papers we have counts for
5 papers
ViPro-2: Unsupervised State Estimation via Integrated Dynamics for Guiding Video Prediction
Patrick Takenaka, Johannes Maucher, Marco F. Huber
Predicting future video frames is a challenging task with many downstream applications. Previous work has shown that procedural knowledge enables deep models for complex dynamical…
Anonymization of Documents for Law Enforcement with Machine Learning
Manuel Eberhardinger, Patrick Takenaka, Daniel Grießhaber +1
The steadily increasing utilization of data-driven methods and approaches in areas that handle sensitive personal information such as in law enforcement mandates an ever increasing…
Classification of Inkjet Printers based on Droplet Statistics
Patrick Takenaka, Manuel Eberhardinger, Daniel Grießhaber +1
Knowing the printer model used to print a given document may provide a crucial lead towards identifying counterfeits or conversely verifying the validity of a real document. Inkjet…
ViPro: Enabling and Controlling Video Prediction for Complex Dynamical Scenarios using Procedural Knowledge
Patrick Takenaka, Johannes Maucher, Marco F. Huber
We propose a novel architecture design for video prediction in order to utilize procedural domain knowledge directly as part of the computational graph of data-driven models. On th…
Guiding Video Prediction with Explicit Procedural Knowledge
Patrick Takenaka, Johannes Maucher, Marco F. Huber
We propose a general way to integrate procedural knowledge of a domain into deep learning models. We apply it to the case of video prediction, building on top of object-centric dee…