4 papers · 1 filter
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…
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…