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:
Aug. 22, 2023

Filed:

Feb. 14, 2020
Applicant:

Naver Corporation, Gyeonggi-do, KR;

Inventors:

Diane Larlus, La Tronche, FR;

Jon Almazan, London, GB;

Cesar De Souza, Grenoble, FR;

Naila Murray, Grenoble, FR;

Rafael Sampaio De Rezende, Grenoble, FR;

Assignee:

NAVER CORPORATION, Gyeonggi-do, KR;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 16/9032 (2019.01); G06F 16/9038 (2019.01); G06F 17/16 (2006.01); G06F 18/22 (2023.01); G06F 18/214 (2023.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06F 16/9032 (2019.01); G06F 16/9038 (2019.01); G06F 16/90332 (2019.01); G06F 17/16 (2013.01); G06F 18/2148 (2023.01); G06F 18/22 (2023.01); G06V 10/761 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01);
Abstract

A training system includes: a training dataset including first objects of a first modality and second objects of a second modality that are associated with the first objects, respectively; a first matrix including first relevance values indicative of relevance between the first objects and the second objects, respectively; a second matrix including second relevance values indicative of relevance between the second objects and the first objects, respectively; and a training module configured to: based on similarities between ones of the second objects, generate a third matrix by selectively adding first additional relevance values to the first matrix; based on the similarities between the ones of the second objects, generate a fourth matrix by selectively adding second additional relevance values to the second matrix; and store the third and fourth matrices in memory of a search module for cross-modal retrieval in response to receipt of search queries.


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