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. 03, 2025

Filed:

Dec. 29, 2022
Applicants:

Rameen Abdal, Los Angeles, CA (US);

Menglei Chai, Los Angeles, CA (US);

Hsin-ying Lee, San Jose, CA (US);

Aliaksandr Siarohin, Los Angeles, CA (US);

Sergey Tulyakov, Santa Monica, CA (US);

Peihao Zhu, Los Angeles, CA (US);

Inventors:

Rameen Abdal, Los Angeles, CA (US);

Menglei Chai, Los Angeles, CA (US);

Hsin-Ying Lee, San Jose, CA (US);

Aliaksandr Siarohin, Los Angeles, CA (US);

Sergey Tulyakov, Santa Monica, CA (US);

Peihao Zhu, Los Angeles, CA (US);

Assignee:

Snap Inc., Santa Monica, CA (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06T 15/02 (2011.01); G06N 3/045 (2023.01); G06N 3/088 (2023.01); G06N 20/00 (2019.01); G06T 11/00 (2006.01);
U.S. Cl.
CPC ...
G06T 15/02 (2013.01); G06N 3/045 (2023.01); G06N 3/088 (2013.01); G06N 20/00 (2019.01); G06T 11/00 (2013.01);
Abstract

Domain adaptation frameworks for producing a 3D avatar generative adversarial network (GAN) capable of generating an avatar based on a single photographic image. The 3D avatar GAN is produced by training a target domain using an artistic dataset. Each artistic dataset includes a plurality of source images, each associated with a style type, such as caricature, cartoon, and comic. The domain adaptation framework in some implementations starts with a source domain that has been trained according to a 3D GAN and a target domain trained with a 2D GAN. The framework fine-tunes the 2D GAN by training it with the artistic datasets. The resulting 3D avatar GAN generates a 3D artistic avatar and an editing module for performing semantic and geometric edits.


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