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:
Apr. 14, 2026

Filed:

May. 08, 2023
Applicant:

Apple Inc., Cupertino, CA (US);

Inventors:

Paul M Bombach, Seattle, WA (US);

James C Arndt, Livermore, CA (US);

David N Chen, Cupertino, CA (US);

Todd E Kramer, New York, NY (US);

Shaun M Poole, Palo Alto, CA (US);

Rupamay Saha, Cupertino, CA (US);

Eugene M. Walden, San Anselmo, CA (US);

Assignee:

Apple Inc., Cupertino, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 21/431 (2011.01); G06F 3/04847 (2022.01); G06F 3/0488 (2022.01); G06F 3/04883 (2022.01); G06T 5/70 (2024.01); G06T 5/73 (2024.01); G06T 5/92 (2024.01); G06T 11/00 (2006.01); G06V 10/70 (2022.01); G11B 27/031 (2006.01); H04N 7/01 (2006.01); H04N 21/472 (2011.01);
U.S. Cl.
CPC ...
H04N 21/4312 (2013.01); G06F 3/04847 (2013.01); G06F 3/0488 (2013.01); G06F 3/04883 (2013.01); G06T 5/70 (2024.01); G06T 5/73 (2024.01); G06T 5/92 (2024.01); G06T 11/001 (2013.01); G06V 10/70 (2022.01); G11B 27/031 (2013.01); H04N 7/0122 (2013.01); H04N 21/47217 (2013.01); G06T 2200/24 (2013.01); G06T 2207/10016 (2013.01);
Abstract

In one or more embodiments, a computing device is configured to modify an original video by applying a machine learning model. The computing device obtains multiple training data sets, with each particular training data set including an original video and a corresponding modified video. One or more frames from the original video are cropped to generate corresponding frames in the corresponding modified video. The computing device trains a machine learning model, using the training data sets, to generate modified videos from original videos such that one or more frames in the original videos are modified to generate corresponding frames in respective modified videos. Once the machine learning model is trained, the computing device obtains a target original video and applies the trained machine learning model to the target original video to generate a target modified video.


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