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:
Jun. 10, 2025

Filed:

Oct. 19, 2022
Applicants:

Santa Clara University, Santa Clara, CA (US);

Kwai Inc., Palo Alto, CA (US);

Inventors:

Yifei Pei, Santa Clara, CA (US);

Ying Liu, Santa Clara, CA (US);

Nam Ling, Santa Clara, CA (US);

Yongxiong Ren, San Jose, CA (US);

Lingzhi Liu, San Jose, CA (US);

Assignees:

SANTA CLARA UNIVERSITY, Santa Clara, CA (US);

KWAI INC., Palo Alto, CA (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 9/00 (2006.01); G06N 3/0455 (2023.01); G06N 3/0475 (2023.01); G06N 3/094 (2023.01); H04N 19/124 (2014.01);
U.S. Cl.
CPC ...
G06T 9/002 (2013.01); G06N 3/0455 (2023.01); G06N 3/0475 (2023.01); G06N 3/094 (2023.01); H04N 19/124 (2014.11);
Abstract

A neural network system, a method and an apparatus for image compression are provided. The neural network may include a generator including an encoder, an entropy estimator, and a decoder, where the encoder receives an input image and generates an encoder output, a plurality of quantized feature entries are obtained based on the encoder output outputted at a last encoder block, the entropy estimator receives the plurality of quantized feature entries and calculates an entropy loss based on the plurality of quantized feature entries, and the decoder receives the plurality of quantized feature entries and generates a reconstructed image. Furthermore, the neural network may include a discriminator that determines whether the reconstructed image different from the input image based on a discriminator loss. Moreover, the generator may determine whether content of the reconstructed image matches content of the input image based on a generator loss including the entropy loss.


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