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:
Mar. 19, 2024

Filed:

Nov. 02, 2021
Applicant:

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

Inventor:

Zixun Sun, Shenzhen, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); A63F 13/52 (2014.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06T 7/11 (2017.01); G06T 15/04 (2011.01); G06T 17/00 (2006.01); G06V 10/44 (2022.01); G06V 10/56 (2022.01); G06V 30/262 (2022.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06F 18/214 (2023.01); A63F 13/52 (2014.09); G06F 18/24 (2023.01); G06T 7/11 (2017.01); G06T 15/04 (2013.01); G06T 17/00 (2013.01); G06V 10/44 (2022.01); G06V 10/56 (2022.01); G06V 30/274 (2022.01); G06N 20/00 (2019.01); G06T 2207/20081 (2013.01);
Abstract

The present disclosure provides methods, apparatus, and storage medium for generating a training sample of a semantic segmentation model. The method includes obtaining an object identifier of a to-be-trained object and a model file corresponding to the object identifier, the model file comprising a three-dimensional model of the to-be-trained object and a skin map set, the skin map set comprising a plurality of solid-color skin maps and a plurality of colorful skin maps; determining transformation models corresponding to the three-dimensional model; generating a plurality of sample image groups corresponding to each transformation model according to the plurality of colorful skin maps and each transformation model; generating a labeled image of the each sample image group according to the object identifier, the plurality of solid-color skin maps, and each transformation model; and generating a training sample of the to-be-trained object according to the labeled image and the each sample image group.


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