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:
Feb. 13, 2024

Filed:

Nov. 11, 2020
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Ji Li, San Jose, CA (US);

Amit Srivastava, San Jose, CA (US);

Mingxi Cheng, Los Angeles, CA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 3/02 (2006.01); G06N 3/088 (2023.01); G06N 5/04 (2023.01); G06F 40/186 (2020.01); G06N 20/00 (2019.01); G06F 40/103 (2020.01); G06V 10/40 (2022.01);
U.S. Cl.
CPC ...
G06F 40/186 (2020.01); G06F 40/103 (2020.01); G06N 3/02 (2013.01); G06N 3/088 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06V 10/40 (2022.01);
Abstract

The present disclosure applies trained artificial intelligence (AI) processing adapted to automatically generating transformations of formatted templates. Pre-existing formatted templates (e.g., slide-based presentation templates) are leveraged by the trained AI processing to automatically generate a plurality of high-quality template transformations. In transforming a formatted template, the trained AI processing not only generates feature transformation of objects thereof but may also provide style transformations where attributes associated with a presentation theme may be modified for a formatted template or set of formatted templates. The trained AI processing is novel in that it is tailored for analysis of feature data of a specific type of formatted template. The trained AI processing converts a formatted template into a feature vector and utilizes conditioned generative modeling to generate one or more transformed templates using a representation of the feature data and feature data from one or more other formatted templates.


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