Eirikur Agustsson | DeepAI

DeepAI AI Chat

Featured Co-authors

Luc Van Gool
414 publications
Wei Li
286 publications
Yu Qiao
242 publications
Liang Lin
216 publications
Luca Benini
202 publications
Radu Timofte
174 publications
Jie Liu
114 publications
Limin Wang
104 publications
Chao Dong
90 publications
Abhinav Gupta
76 publications
Vittorio Ferrari
76 publications

∙ 05/26/2023

High-Fidelity Image Compression with Score-based Generative Models

Despite the tremendous success of diffusion generative models in text-to...

0 Emiel Hoogeboom, et al. ∙

∙ 04/14/2023

M2T: Masking Transformers Twice for Faster Decoding

We show how bidirectional transformers trained for masked token predicti...

0 Fabian Mentzer, et al. ∙

∙ 12/28/2022

Multi-Realism Image Compression with a Conditional Generator

By optimizing the rate-distortion-realism trade-off, generative compress...

0 Eirikur Agustsson, et al. ∙

∙ 06/15/2022

VCT: A Video Compression Transformer

We show how transformers can be used to vastly simplify neural video com...

0 Fabian Mentzer, et al. ∙

∙ 07/26/2021

Towards Generative Video Compression

We present a neural video compression method based on generative adversa...

5 Fabian Mentzer, et al. ∙

∙ 02/18/2021

On the advantages of stochastic encoders

Stochastic encoders have been used in rate-distortion theory and neural ...

0 Lucas Theis, et al. ∙

∙ 07/06/2020

Nonlinear Transform Coding

We review a class of methods that can be collected under the name nonlin...

0 Johannes Ballé, et al. ∙

∙ 06/17/2020

High-Fidelity Generative Image Compression

We extensively study how to combine Generative Adversarial Networks and ...

3 Fabian Mentzer, et al. ∙

∙ 06/17/2020

Universally Quantized Neural Compression

A popular approach to learning encoders for lossy compression is to use ...

7 Eirikur Agustsson, et al. ∙

∙ 12/05/2018

Interactive Full Image Segmentation

We address the task of interactive full image annotation, where the goal...

10 Eirikur Agustsson, et al. ∙

∙ 11/30/2018

Practical Full Resolution Learned Lossless Image Compression

We propose the first practical learned lossless image compression system...

6 Fabian Mentzer, et al. ∙

∙ 10/03/2018

PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report

This paper reviews the first challenge on efficient perceptual image enh...

2 Andrey Ignatov, et al. ∙

∙ 05/28/2018

Deep Generative Models for Distribution-Preserving Lossy Compression

We propose and study the problem of distribution-preserving lossy compre...

2 Michael Tschannen, et al. ∙

∙ 04/09/2018

Generative Adversarial Networks for Extreme Learned Image Compression

We propose a framework for extreme learned image compression based on Ge...

0 Eirikur Agustsson, et al. ∙

∙ 03/16/2018

Towards Image Understanding from Deep Compression without Decoding

Motivated by recent work on deep neural network (DNN)-based image compre...

0 Robert Torfason, et al. ∙

∙ 01/12/2018

Conditional Probability Models for Deep Image Compression

Deep Neural Networks trained as image auto-encoders have recently emerge...

0 Fabian Mentzer, et al. ∙

∙ 12/19/2017

ComboGAN: Unrestrained Scalability for Image Domain Translation

This year alone has seen unprecedented leaps in the area of learning-bas...

0 Asha Anoosheh, et al. ∙

∙ 12/12/2017

Logo Synthesis and Manipulation with Clustered Generative Adversarial Networks

Designing a logo for a new brand is a lengthy and tedious back-and-forth...

0 Alexander Sage, et al. ∙

∙ 11/06/2017

Optimal transport maps for distribution preserving operations on latent spaces of Generative Models

Generative models such as Variational Auto Encoders (VAEs) and Generativ...

0 Eirikur Agustsson, et al. ∙

∙ 08/09/2017

WebVision Database: Visual Learning and Understanding from Web Data

In this paper, we present a study on learning visual recognition models ...

0 Wen Li, et al. ∙

∙ 05/16/2017

WebVision Challenge: Visual Learning and Understanding With Web Data

We present the 2017 WebVision Challenge, a public image recognition chal...

0 Wen Li, et al. ∙

∙ 04/03/2017

Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations

We present a new approach to learn compressible representations in deep ...

0 Eirikur Agustsson, et al. ∙

∙ 05/30/2016

k2-means for fast and accurate large scale clustering

We propose k^2-means, a new clustering method which efficiently copes wi...

0 Eirikur Agustsson, et al. ∙

∙ 03/13/2014

Neighborhood Selection for Thresholding-based Subspace Clustering

Subspace clustering refers to the problem of clustering high-dimensional...

0 Reinhard Heckel, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world