1.4k citations · 1.5k across the 13 of their papers we have counts for
17 papers
Advancing The Rate-Distortion-Computation Frontier For Neural Image Compression
David Minnen, Nick Johnston
The rate-distortion performance of neural image compression models has exceeded the state-of-the-art for non-learned codecs, but neural codecs are still far from widespread deploym…
The Need for Medically Aware Video Compression in Gastroenterology
Joel Shor, Nick Johnston
Compression is essential to storing and transmitting medical videos, but the effect of compression on downstream medical tasks is often ignored. Furthermore, systems in practice re…
LVAC: Learned Volumetric Attribute Compression for Point Clouds using Coordinate Based Networks
Berivan Isik, Philip A. Chou, Sung Jin Hwang +2
We consider the attributes of a point cloud as samples of a vector-valued volumetric function at discrete positions. To compress the attributes given the positions, we compress the…
Neural Video Compression using GANs for Detail Synthesis and Propagation
Fabian Mentzer, Eirikur Agustsson, Johannes Ballé +3
We present the first neural video compression method based on generative adversarial networks (GANs). Our approach significantly outperforms previous neural and non-neural video co…
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…