1.1k citations · 1.7k across the 5 of their papers we have counts for
6 papers
A differentiable Gaussian Prototype Layer for explainable Segmentation
Michael Gerstenberger, Steffen Maaß, Peter Eisert +1
We introduce a Gaussian Prototype Layer for gradient-based prototype learning and demonstrate two novel network architectures for explainable segmentation one of which relies on re…
From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation
Reduan Achtibat, Maximilian Dreyer, Ilona Eisenbraun +4
The field of eXplainable Artificial Intelligence (XAI) aims to bring transparency to today's powerful but opaque deep learning models. While local XAI methods explain individual pr…
Curiously Effective Features for Image Quality Prediction
Sören Becker, Thomas Wiegand, Sebastian Bosse
The performance of visual quality prediction models is commonly assumed to be closely tied to their ability to capture perceptually relevant image aspects. Models are thus either b…
Kalman Filter-based Head Motion Prediction for Cloud-based Mixed Reality
Serhan Gül, Sebastian Bosse, Dimitri Podborski +2
Volumetric video allows viewers to experience highly-realistic 3D content with six degrees of freedom in mixed reality (MR) environments. Rendering complex volumetric videos can re…
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment
Sebastian Bosse, Dominique Maniry, Klaus-Robert Müller +2
We present a deep neural network-based approach to image quality assessment (IQA). The network is trained end-to-end and comprises ten convolutional layers and five pooling layers…
A Haar Wavelet-Based Perceptual Similarity Index for Image Quality Assessment
Rafael Reisenhofer, Sebastian Bosse, Gitta Kutyniok +1
In most practical situations, the compression or transmission of images and videos creates distortions that will eventually be perceived by a human observer. Vice versa, image and…