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:
Jan. 05, 2021

Filed:

Jun. 21, 2019
Applicant:

Facebook Technologies, Llc, Menlo Park, CA (US);

Inventors:

Jason Saragih, Pittsburgh, PA (US);

Shih-En Wei, Pittsburgh, PA (US);

Assignee:

Facebook Technologies, LLC, Menlo Park, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 13/40 (2011.01); G06T 7/00 (2017.01); G06T 7/70 (2017.01); G06T 1/20 (2006.01); H04N 5/247 (2006.01);
U.S. Cl.
CPC ...
G06T 13/40 (2013.01); G06T 1/20 (2013.01); G06T 7/70 (2017.01); G06T 7/97 (2017.01); G06T 2207/10048 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30201 (2013.01); H04N 5/247 (2013.01);
Abstract

In one embodiment, a computing system may access a plurality of first captured images that are captured in a first spectral domain, generate, using a first machine-learning model, a plurality of first domain-transferred images based on the first captured images, wherein the first domain-transferred images are in a second spectral domain, render, based on a first avatar, a plurality of first rendered images comprising views of the first avatar, and update the first machine-learning model based on comparisons between the first domain-transferred images and the first rendered images, wherein the first machine-learning model is configured to translate images in the first spectral domain to the second spectral domain. The system may also generate, using a second machine-learning model, the first avatar based on the first captured images. The first avatar may be rendered using a parametric face model based on a plurality of avatar parameters.


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