Towards image compression with perfect realism at ultra-low bitrates

March 14, 2024


Image codecs are typically optimized to trade-off bitrate vs. distortion metrics. At low bitrates, this leads to compression artefacts which are easily perceptible, even when training with perceptual or adversarial losses. To improve image quality and remove dependency on the bitrate we propose to decode with iterative diffusion models. We condition the decoding process on a vector-quantized image representation, as well as a global image description to provide additional context. We dub our model `PerCo'' for ``perceptual compression'', and compare it to state-of-the-art codecs at rates from 0.1 down to 0.003 bits per pixel. The latter rate is more than an order of magnitude smaller than those considered in most prior work, compressing a 512x768 Kodak image with less than 153 bytes. Despite this ultra-low bitrate, our approach maintains the ability to reconstruct realistic images. We find that our model leads to reconstructions with state-of-the-art visual quality as measured by FID and KID. As predicted by rate-distortion-perception theory, visual quality is less dependent on the bitrate than previous methods.

Download the Paper


Written by

Marlene Careil

Matthew Muckley

Jakob Verbeek

Stephane Lathuiliere



Research Topics

Computer Vision

Related Publications

May 06, 2024



Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint

Haoyue Tang, Tian Xie

May 06, 2024

April 23, 2024


Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on Aerial Lidar

Jamie Tolan, Eric Yang, Ben Nosarzewski, Guillaume Couairon, Huy Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie, Edward Saenz

April 23, 2024

April 23, 2024



Generating Illustrated Instructions

Sachit Menon, Ishan Misra, Rohit Girdhar

April 23, 2024

April 18, 2024


Imagine Flash: Accelerating Emu Diffusion Models with Backward Distillation

Jonas Kohler, Albert Pumarola, Edgar Schoenfeld, Artsiom Sanakoyeu, Roshan Sumbaly, Peter Vajda, Ali Thabet

April 18, 2024

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.