The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 10, 2024

Filed:

Mar. 06, 2020
Applicants:

Disney Enterprises, Inc., Burbank, CA (US);

Eth Zürich, Zürich, CH;

Inventors:

Abdelaziz Djelouah, Zürich, CH;

Leonhard Markus Helminger, Zürich, CH;

Scott Labrozzi, Cary, NC (US);

Yuanyi Xue, Kensington, CA (US);

Erika Varis Doggett, Los Angeles, CA (US);

Jared McPhillen, Glendale, CA (US);

Christopher Richard Schroers, Zürich, CH;

Assignees:

Disney Enterprises, Inc., Burbank, CA (US);

ETH Zurich, Zurich, CH;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 19/60 (2014.01); G06T 9/00 (2006.01); H04N 19/126 (2014.01); H04N 19/91 (2014.01);
U.S. Cl.
CPC ...
G06T 9/002 (2013.01); H04N 19/126 (2014.11); H04N 19/60 (2014.11); H04N 19/91 (2014.11);
Abstract

According to one implementation, an image compression system includes a computing platform having a hardware processor and a system memory storing a software code. The hardware processor executes the software code to receive an input image, transform the input image to a latent space representation of the input image, and quantize the latent space representation of the input image to produce multiple quantized latents. The hardware processor further executes the software code to encode the quantized latents using a probability density function of the latent space representation of the input image, to generate a bitstream, and convert the bitstream into an output image corresponding to the input image. The probability density function of the latent space representation of the input image is obtained based on a normalizing flow mapping of one of the input image or the latent space representation of the input image.


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