15 citations · 18 across the 3 of their papers we have counts for
3 papers
Learning Neural Light Transport
Paul Sanzenbacher, Lars Mescheder, Andreas Geiger
In recent years, deep generative models have gained significance due to their ability to synthesize natural-looking images with applications ranging from virtual reality to data au…
Learning to Predict Ego-Vehicle Poses for Sampling-Based Nonholonomic Motion Planning
Holger Banzhaf, Paul Sanzenbacher, Ulrich Baumann +1
Sampling-based motion planning is an effective tool to compute safe trajectories for automated vehicles in complex environments. However, a fast convergence to the optimal solution…
Automated Deep Photo Style Transfer
Sebastian Penhouët, Paul Sanzenbacher
Photorealism is a complex concept that cannot easily be formulated mathematically. Deep Photo Style Transfer is an attempt to transfer the style of a reference image to a content i…