264 citations · 320 across the 7 of their papers we have counts for
16 papers
Towards Multimodal Depth Estimation from Light Fields
Titus Leistner, Radek Mackowiak, Lynton Ardizzone +2
Light field applications, especially light field rendering and depth estimation, developed rapidly in recent years. While state-of-the-art light field rendering methods handle semi…
Review of Disentanglement Approaches for Medical Applications -- Towards Solving the Gordian Knot of Generative Models in Healthcare
Jana Fragemann, Lynton Ardizzone, Jan Egger +1
Deep neural networks are commonly used for medical purposes such as image generation, segmentation, or classification. Besides this, they are often criticized as black boxes as the…
Emission-line diagnostics of HII regions using conditional Invertible Neural Networks
Da Eun Kang, Eric W. Pellegrini, Lynton Ardizzone +4
Young massive stars play an important role in the evolution of the interstellar medium (ISM) and the self-regulation of star formation in giant molecular clouds (GMCs) by injecting…
Conditional Invertible Neural Networks for Diverse Image-to-Image Translation
Lynton Ardizzone, Jakob Kruse, Carsten Lüth +3
We introduce a new architecture called a conditional invertible neural network (cINN), and use it to address the task of diverse image-to-image translation for natural images. This…
Benchmarking Invertible Architectures on Inverse Problems
Jakob Kruse, Lynton Ardizzone, Carsten Rother +1
Recent work demonstrated that flow-based invertible neural networks are promising tools for solving ambiguous inverse problems. Following up on this, we investigate how ten inverti…
Representing Ambiguity in Registration Problems with Conditional Invertible Neural Networks
Darya Trofimova, Tim Adler, Lisa Kausch +5
Image registration is the basis for many applications in the fields of medical image computing and computer assisted interventions. One example is the registration of 2D X-ray imag…