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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.

Patent No.:

US 12229881 B1

PDFFull Text
Date of Patent:
Feb. 18, 2025

Filed:

Mar. 29, 2022

Method and apparatus for generating three-dimensional face model, computer device, and storage medium

Applicant:

Tencent Technology (Shenzhen) Company Limited, Shenzhen, CN;

Inventors:

Wenpan Li, Shenzhen, CN;

Linchao Bao, Shenzhen, CN;

Xiangkai Lin, Shenzhen, CN;

Assignee:

TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED, Shenzhen, CN;

Attorney:

ANOVA LAW GROUP PLLC

Primary Examiner:

Xiao M Wu

Assistant Examiner:

Scott E Sonners

Int. Cl.
CPC ...
G06T 17/00 (2006.01); G06T 3/60 (2024.01); G06T 7/40 (2017.01); G06T 7/55 (2017.01); G06T 7/70 (2017.01); G06V 10/22 (2022.01); G06V 10/56 (2022.01); G06V 10/764 (2022.01); G06V 40/16 (2022.01); G06V 40/18 (2022.01);
U.S. Cl.
CPC ...
G06T 17/00 (2013.01); G06T 3/60 (2013.01); G06T 7/40 (2013.01); G06T 7/55 (2017.01); G06T 7/70 (2017.01); G06V 10/225 (2022.01); G06V 10/56 (2022.01); G06V 10/764 (2022.01); G06V 40/168 (2022.01); G06V 40/172 (2022.01); G06V 40/174 (2022.01); G06V 40/18 (2022.01); G06T 2200/08 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30201 (2013.01); G06T 2207/30208 (2013.01); G06T 2210/56 (2013.01);
Abstract

Embodiments of this application disclose a method and an apparatus for generating a three-dimensional face model. The method includes obtaining a plurality of target face images and a plurality of depth images corresponding to the plurality of target face images, the plurality of target face images comprising a same face; obtaining, according to an image type of each target face image, a regional face image that is in each target face image and that corresponds to the image type of each target face image, the image type comprising a front face type, a left face type, a right face type, or a head-up type; obtaining a regional depth image in a corresponding depth image according to the regional face image; and performing image fusion based on the plurality of obtained regional face images and the plurality of obtained regional depth images, to generate a three-dimensional face model.

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