Fabian Mentzer | DeepAI

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∙ 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. ∙

∙ 06/17/2022

Lossy Compression with Gaussian Diffusion

We describe a novel lossy compression approach called DiffC which is bas...

1 Lucas Theis, 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. ∙

∙ 06/24/2020

Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model

The past few years have witnessed increasing interests in applying deep ...

21 Ren Yang, 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. ∙

∙ 03/23/2020

Learning Better Lossless Compression Using Lossy Compression

We leverage the powerful lossy image compression algorithm BPG to build ...

9 Fabian Mentzer, et al. ∙

∙ 03/04/2020

Learning for Video Compression with Hierarchical Quality and Recurrent Enhancement

The recent years have witnessed the great potential of deep learning for...

23 Ren Yang, 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 09/26/2016

Deep Structured Features for Semantic Segmentation

We propose a highly structured neural network architecture for semantic ...

0 Michael Tschannen, et al. ∙

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