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. 20, 2026

Filed:

Nov. 21, 2022
Applicants:

Lemon Inc., Grand Cayman, KY;

Beijing Zitiao Network Technology Co., Ltd., Beijing, CN;

Inventors:

Xiaojie Jin, Los Angeles, CA (US);

Sen Pei, Beijing, CN;

Assignees:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 20/40 (2022.01); G06N 3/0464 (2023.01); G06N 3/09 (2023.01); G06V 10/62 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); H04N 21/44 (2011.01);
U.S. Cl.
CPC ...
G06V 20/46 (2022.01); G06V 10/62 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/806 (2022.01); G06V 10/82 (2022.01); G06V 20/41 (2022.01);
Abstract

Systems and methods are provided that include a processor executing a video classifying program to receive an input video, sample video frames from the input video, extract frame-wise spatial features from the video frames using a convolutional neural network, extract a frame-wise temporal feature for each video frame, aggregate the frame-wise spatial features and the frame-wise temporal feature for each video frame to provide a temporal context to the frame-wise spatial features, input the aggregated frame-wise spatial features and the frame-wise temporal feature for each frame into a transformer encoder to obtain temporal-aware feature representations of the video frames, input the feature representations into a feedforward network model to obtain feedforward-transformed features, obtain a parameter by inputting each feedforward-transformed feature and a set of highlight prototypes into a function comparing the feedforward-transformed features to the set of highlight prototypes, classify the video frames as highlights based on the calculated parameter.


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