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. 20, 2025

Filed:

Apr. 26, 2022
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Xuhui Jia, Seattle, WA (US);

Kai Han, Bristol, GB;

Assignee:

Google LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/82 (2022.01); G06V 10/42 (2022.01); G06V 10/44 (2022.01); G06V 10/74 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01);
U.S. Cl.
CPC ...
G06V 10/774 (2022.01); G06V 10/42 (2022.01); G06V 10/44 (2022.01); G06V 10/761 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing novel category discovery. One of the methods includes generating first local feature tensors from a first training image; obtaining previous local feature tensors generated from a previous training image; generating a first similarity tensor representing a similarity between the first local feature tensors and the previous local feature tensors; obtaining a second similarity tensor for a second training image; processing, using a neural network, the first training image to generate a first training output representing a class prediction for the first training image; obtaining a second training output representing a class prediction for the second training image; and generating an update to the neural network from (i) a similarity between the first similarity tensor and the second similarity tensor and (ii) a similarity between the first training output and the second training output.


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