2 citations · 3 across the 6 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
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…