43 citations · 74 across the 4 of their papers we have counts for
5 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…
Generative Classifiers as a Basis for Trustworthy Image Classification
Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe +1
With the maturing of deep learning systems, trustworthiness is becoming increasingly important for model assessment. We understand trustworthiness as the combination of explainabil…
Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification
Lynton Ardizzone, Radek Mackowiak, Carsten Rother +1
The Information Bottleneck (IB) objective uses information theory to formulate a task-performance versus robustness trade-off. It has been successfully applied in the standard disc…
Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift
Titus Leistner, Hendrik Schilling, Radek Mackowiak +2
We propose a method for depth estimation from light field data, based on a fully convolutional neural network architecture. Our goal is to design a pipeline which achieves highly a…
CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation
Radek Mackowiak, Philip Lenz, Omair Ghori +3
State of the art methods for semantic image segmentation are trained in a supervised fashion using a large corpus of fully labeled training images. However, gathering such a corpus…