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. 07, 2025

Filed:

Feb. 03, 2023
Applicant:

Adobe Inc., San Jose, CA (US);

Inventors:

Xiaojuan Wang, Bellevue, WA (US);

Richard Zhang, San Francisco, CA (US);

Taesung Park, Albany, CA (US);

Yang Zhou, San Jose, CA (US);

Elya Shechtman, Seattle, WA (US);

Assignee:

Adobe Inc., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 21/234 (2011.01); G06V 10/771 (2022.01); G06V 10/82 (2022.01); H04N 21/81 (2011.01);
U.S. Cl.
CPC ...
H04N 21/8153 (2013.01); G06V 10/771 (2022.01); G06V 10/82 (2022.01); H04N 21/23424 (2013.01);
Abstract

The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize machine learning to generate a sequence of transition frames for a gap in a clipped digital video. For example, the disclosed system receives a clipped digital video that includes a pre-cut frame prior to a gap in the clipped digital video and a post-cut frame following the gap in the clipped digital video. Moreover, the disclosed system utilizes a natural motion sequence model to generates a sequence of transition keypoint maps between the pre-cut frame and the post-cut frame. Furthermore, using a generative neural network, the disclosed system generates a sequence of transition frames for the gap in the clipped digital video from the sequence of transition keypoint maps.


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