431 citations · 2.5k across the 40 of their papers we have counts for
7 papers · 1 filter
Recent Advances in Autoencoder-Based Representation Learning
Michael Tschannen, Olivier Bachem, Mario Lucic
Learning useful representations with little or no supervision is a key challenge in artificial intelligence. We provide an in-depth review of recent advances in representation lear…
Practical Full Resolution Learned Lossless Image Compression
Fabian Mentzer, Eirikur Agustsson, Michael Tschannen +2
We propose the first practical learned lossless image compression system, L3C, and show that it outperforms the popular engineered codecs, PNG, WebP and JPEG 2000. At the core of o…
Born Again Neural Networks
Tommaso Furlanello, Zachary C. Lipton, Michael Tschannen +2
Knowledge Distillation (KD) consists of transferring “knowledge†from one machine learning model (the teacher) to another (the student). Commonly, the teacher is a high-capacit…
Deep Generative Models for Distribution-Preserving Lossy Compression
Michael Tschannen, Eirikur Agustsson, Mario Lucic
We propose and study the problem of distribution-preserving lossy compression. Motivated by recent advances in extreme image compression which allow to maintain artifact-free recon…
Generative Adversarial Networks for Extreme Learned Image Compression
Eirikur Agustsson, Michael Tschannen, Fabian Mentzer +2
We present a learned image compression system based on GANs, operating at extremely low bitrates. Our proposed framework combines an encoder, decoder/generator and a multi-scale di…
Towards Image Understanding from Deep Compression without Decoding
Robert Torfason, Fabian Mentzer, Eirikur Agustsson +3
Motivated by recent work on deep neural network (DNN)-based image compression methods showing potential improvements in image quality, savings in storage, and bandwidth reduction,…
Conditional Probability Models for Deep Image Compression
Fabian Mentzer, Eirikur Agustsson, Michael Tschannen +2
Deep Neural Networks trained as image auto-encoders have recently emerged as a promising direction for advancing the state-of-the-art in image compression. The key challenge in lea…