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:
Aug. 05, 2025

Filed:

Jul. 15, 2022
Applicant:

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

Inventors:

Iason Kokkinos, London, GB;

Georgios Papandreou, London, GB;

Riza Alp Guler, London, GB;

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 40/10 (2022.01); G06F 17/18 (2006.01); G06F 18/22 (2023.01); G06F 18/25 (2023.01); G06T 5/50 (2006.01); G06T 11/00 (2006.01); G06V 10/74 (2022.01); G06V 10/80 (2022.01); G06V 20/64 (2022.01);
U.S. Cl.
CPC ...
G06T 11/001 (2013.01); G06F 17/18 (2013.01); G06F 18/22 (2023.01); G06F 18/253 (2023.01); G06T 5/50 (2013.01); G06V 10/74 (2022.01); G06V 10/806 (2022.01); G06V 20/647 (2022.01); G06V 40/103 (2022.01); G06T 2207/20084 (2013.01);
Abstract

Aspects of the present disclosure involve a system and a method for performing operations comprising: receiving a two-dimensional continuous surface representation of a three-dimensional object, the continuous surface comprising a plurality of landmark locations; determining a first set of soft membership functions based on a relative location of points in the two-dimensional continuous surface representation and the landmark locations; receiving a two-dimensional input image, the input image comprising an image of the object; extracting a plurality of features from the input image using a feature recognition model; generating an encoded. feature representation of the extracted features using the first set of soft membership functions; generating a dense feature representation of the extracted features from the encoded representation using a second set of soft membership functions; and processing the second set of soft membership functions and dense feature representation using a neural image decoder model to generate an output image.


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