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:
May. 12, 2026

Filed:

Jan. 30, 2023
Applicant:

Naver Corporation, Gyeonggi-do, KR;

Inventors:

Jérome Revaud, Meylan, FR;

Vincent Leroy, Laval, FR;

Philippe Weinzaepfel, Montbonnot-Saint-Martin, FR;

Boris Chidlovskii, Meylan, FR;

Assignee:

NAVER CORPORATION, Gyeonggi-Do, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/771 (2022.01); G06T 3/40 (2006.01); G06T 7/11 (2017.01); G06V 10/75 (2022.01); G06V 10/82 (2022.01);
U.S. Cl.
CPC ...
G06V 10/771 (2022.01); G06T 3/40 (2013.01); G06T 7/11 (2017.01); G06V 10/751 (2022.01); G06V 10/82 (2022.01); G06T 2207/20016 (2013.01); G06T 2207/20081 (2013.01);
Abstract

A computer-implemented method includes: obtaining a pair of images depicting a same scene, the pair of images including a first image with a first pixel grid and a second image with a second pixel grid, the first pixel grid different than the second pixel grid; by a neural network module having a first set of parameters: generating a first feature map based on the first image; and generating a second feature map based on the second image; determining a first correlation volume based on the first and second feature maps; iteratively determining a second correlation volume based on the first correlation volume; determining a loss for the first and second feature maps based on the second correlation volume; generating a second set of the parameters based on minimizing a loss function using the loss; and updating the neural network module to include the second set of parameters.


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