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20122022
most citedVariational image compression with a scale hyperprior

1.4k citations · 1.6k across the 7 of their papers we have counts for

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8 papers · 1 filter

cs.CV2022★ 39 cited

VCT: A Video Compression Transformer

Fabian Mentzer, George Toderici, David Minnen +4

We show how transformers can be used to vastly simplify neural video compression. Previous methods have been relying on an increasing number of architectural biases and priors, inc…

cs.CV2018★ 1 cited

Towards a Semantic Perceptual Image Metric

Troy Chinen, Johannes Ballé, Chunhui Gu +8

We present a full reference, perceptual image metric based on VGG-16, an artificial neural network trained on object classification. We fit the metric to a new database based on 14…

cs.CV2018

Image-Dependent Local Entropy Models for Learned Image Compression

David Minnen, George Toderici, Saurabh Singh +2

The leading approach for image compression with artificial neural networks (ANNs) is to learn a nonlinear transform and a fixed entropy model that are optimized for rate-distortion…

cs.CV2018

Spatially adaptive image compression using a tiled deep network

David Minnen, George Toderici, Michele Covell +6

Deep neural networks represent a powerful class of function approximators that can learn to compress and reconstruct images. Existing image compression algorithms based on neural n…

cs.CV2017★ 9 cited

Target-Quality Image Compression with Recurrent, Convolutional Neural Networks

Michele Covell, Nick Johnston, David Minnen +5

We introduce a stop-code tolerant (SCT) approach to training recurrent convolutional neural networks for lossy image compression. Our methods introduce a multi-pass training method…

cs.CV2017★ 26 cited

Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networks

Nick Johnston, Damien Vincent, David Minnen +6

We propose a method for lossy image compression based on recurrent, convolutional neural networks that outperforms BPG (4:2:0 ), WebP, JPEG2000, and JPEG as measured by MS-SSIM. We…

cs.CV2016

Full Resolution Image Compression with Recurrent Neural Networks

George Toderici, Damien Vincent, Nick Johnston +4

This paper presents a set of full-resolution lossy image compression methods based on neural networks. Each of the architectures we describe can provide variable compression rates…

cs.CV2015★ 116 cited

Variable Rate Image Compression with Recurrent Neural Networks

George Toderici, Sean M. O'Malley, Sung Jin Hwang +5

A large fraction of Internet traffic is now driven by requests from mobile devices with relatively small screens and often stringent bandwidth requirements. Due to these factors, i…