activity
20182023
most citedSteered Mixture-of-Experts Autoencoder Design for Real-Time Image Modelling and Denoising

2 citations · 3 across the 6 of their papers we have counts for

collaborators

7 papers

eess.IV2023★ 2 cited

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…

eess.IV2023

Steered Mixture of Experts Regression for Image Denoising with Multi-Model-Inference

Aytac Özkan, Yi-Hsin Li, Thomas Sikora

In this paper we introduce a novel block-based regression strategy for image denoising based on edge-aware Steered-Mixture-of-Experts (SMoE) models. SMoEs provide very sparse image…

eess.IV2022★ 1 cited

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…

eess.IV2022

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…

eess.IV2022

Accelerated Deep Lossless Image Coding with Unified Paralleleized GPU Coding Architecture

Benjamin Lukas Cajus Barzen, Fedor Glazov, Jonas Geistert +1

We propose Deep Lossless Image Coding (DLIC), a full resolution learned lossless image compression algorithm. Our algorithm is based on a neural network combined with an entropy en…

cs.CV2019

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…

cs.CV2018

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…