2 citations · 3 across the 3 of their papers we have counts for
9 papers
Challenging the Universal Representation of Deep Models for 3D Point Cloud Registration
David Bojanić, Kristijan Bartol, Josep Forest +3
Learning universal representations across different applications domain is an open research problem. In fact, finding universal architecture within the same application but across…
Real-time Visualization of Stream-based Monitoring Data
Jan Baumeister, Bernd Finkbeiner, Stefan Gumhold +1
Stream-based runtime monitors are used in safety-critical applications such as Unmanned Aerial Systems (UAS) to compute comprehensive statistics and logical assessments of system h…
FuseVis: Interpreting neural networks for image fusion using per-pixel saliency visualization
Nishant Kumar, Stefan Gumhold
Image fusion helps in merging two or more images to construct a more informative single fused image. Recently, unsupervised learning based convolutional neural networks (CNN) have…
Visualisation of Medical Image Fusion and Translation for Accurate Diagnosis of High Grade Gliomas
Nishant Kumar, Nico Hoffmann, Matthias Kirsch +1
The medical image fusion combines two or more modalities into a single view while medical image translation synthesizes new images and assists in data augmentation. Together, these…
Reinforced Feature Points: Optimizing Feature Detection and Description for a High-Level Task
Aritra Bhowmik, Stefan Gumhold, Carsten Rother +1
We address a core problem of computer vision: Detection and description of 2D feature points for image matching. For a long time, hand-crafted designs, like the seminal SIFT algori…
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…