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:
Sep. 03, 2024

Filed:

Feb. 02, 2023
Applicant:

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

Inventors:

Pranav Vineet Aggarwal, San Jose, CA (US);

Zhe Lin, Fremont, CA (US);

Baldo Antonio Faieta, San Francisco, CA (US);

Saeid Antonio Motiian, San Francisco, CA (US);

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/00 (2019.01); G06F 16/538 (2019.01); G06F 16/583 (2019.01); G06F 18/21 (2023.01); G06F 18/22 (2023.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); G06V 10/82 (2022.01); G06V 10/94 (2022.01); G06V 30/19 (2022.01); G06V 30/262 (2022.01); G06F 40/30 (2020.01); G10L 15/22 (2006.01);
U.S. Cl.
CPC ...
G06F 16/583 (2019.01); G06F 16/538 (2019.01); G06F 18/21 (2023.01); G06F 18/22 (2023.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06V 10/82 (2022.01); G06V 10/945 (2022.01); G06V 30/19147 (2022.01); G06V 30/1916 (2022.01); G06V 30/19173 (2022.01); G06V 30/274 (2022.01); G06F 40/30 (2020.01); G10L 15/22 (2013.01);
Abstract

Visually guided machine-learning language model and embedding techniques are described that overcome the challenges of conventional techniques in a variety of ways. In one example, a model is trained to support a visually guided machine-learning embedding space that supports visual intuition as to 'what' is represented by text. The visually guided language embedding space supported by the model, once trained, may then be used to support visual intuition as part of a variety of functionality. In one such example, the visually guided language embedding space as implemented by the model may be leveraged as part of a multi-modal differential search to support search of digital images and other digital content with real-time focus adaptation which overcomes the challenges of conventional techniques.


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