2 citations · 3 across the 5 of their papers we have counts for
7 papers
A Multi-Sensor Dataset for Monitoring the Operational Environment of Rail Vehicles
Claudio Diotallevi, Rodrigo Gudiño, Zaharia Pachalieva +5
Reliable environment monitoring is essential for the safe and efficient operation of automated railway systems, covering all Grades of Automation (GoA), from partially automated (G…
Enclosing Prototypical Variational Autoencoder for Explainable Out-of-Distribution Detection
Conrad Orglmeister, Erik Bochinski, Volker Eiselein +1
Understanding the decision-making and trusting the reliability of Deep Machine Learning Models is crucial for adopting such methods to safety-relevant applications. We extend self-…
Steered Mixture-of-Experts Autoencoder Design for Real-Time Image Modelling and Denoising
Elvira Fleig, Erik Bochinski, Thomas Sikora
Research in the past years introduced Steered Mixture-of-Experts (SMoE) as a framework to form sparse, edge-aware models for 2D- and higher dimensional pixel data, applicable to co…
Sparse Video Representation Using Steered Mixture-of-Experts With Global Motion Compensation
Rolf Jongebloed, Erik Bochinski, Thomas Sikora
Steered-Mixtures-of Experts (SMoE) present a unified framework for sparse representation and compression of image data with arbitrary dimensionality. Recent work has shown great im…
Edge-Aware Autoencoder Design for Real-Time Mixture-of-Experts Image Compression
Elvira Fleig, Jonas Geistert, Erik Bochinski +2
Steered-Mixtures-of-Experts (SMoE) models provide sparse, edge-aware representations, applicable to many use-cases in image processing. This includes denoising, super-resolution an…
Video-based Bottleneck Detection utilizing Lagrangian Dynamics in Crowded Scenes
Maik Simon, Markus Küchhold, Tobias Senst +2
Avoiding bottleneck situations in crowds is critical for the safety and comfort of people at large events or in public transportation. Based on the work of Lagrangian motion analys…
Optical Flow Dataset and Benchmark for Visual Crowd Analysis
Gregory Schröder, Tobias Senst, Erik Bochinski +1
The performance of optical flow algorithms greatly depends on the specifics of the content and the application for which it is used. Existing and well established optical flow data…