121 citations · 319 across the 7 of their papers we have counts for
4 papers · 1 filter
Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data
Sebastian Lunz, Yingzhen Li, Andrew Fitzgibbon +1
Recent work has shown the ability to learn generative models for 3D shapes from only unstructured 2D images. However, training such models requires differentiating through the rast…
Task adapted reconstruction for inverse problems
Jonas Adler, Sebastian Lunz, Olivier Verdier +2
The paper considers the problem of performing a task defined on a model parameter that is only observed indirectly through noisy data in an ill-posed inverse problem. A key aspect…
Banach Wasserstein GAN
Jonas Adler, Sebastian Lunz
Wasserstein Generative Adversarial Networks (WGANs) can be used to generate realistic samples from complicated image distributions. The Wasserstein metric used in WGANs is based on…
Adversarial Regularizers in Inverse Problems
Sebastian Lunz, Ozan Öktem, Carola-Bibiane Schönlieb
Inverse Problems in medical imaging and computer vision are traditionally solved using purely model-based methods. Among those variational regularization models are one of the most…