256 citations · 334 across the 5 of their papers we have counts for
3 papers · 1 filter
End-to-end Learning of Compressible Features
Saurabh Singh, Sami Abu-El-Haija, Nick Johnston +3
Pre-trained convolutional neural networks (CNNs) are powerful off-the-shelf feature generators and have been shown to perform very well on a variety of tasks. Unfortunately, the ge…
Nonlinear Transform Coding
Johannes Ballé, Philip A. Chou, David Minnen +5
We review a class of methods that can be collected under the name nonlinear transform coding (NTC), which over the past few years have become competitive with the best linear trans…
High-Fidelity Generative Image Compression
Fabian Mentzer, George Toderici, Michael Tschannen +1
We extensively study how to combine Generative Adversarial Networks and learned compression to obtain a state-of-the-art generative lossy compression system. In particular, we inve…