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:
Jan. 14, 2025

Filed:

Sep. 12, 2023
Applicant:

Snap Inc., Santa Monica, CA (US);

Inventors:

Shenlong Wang, Toronto, CA;

Linjie Luo, Los Angeles, CA (US);

Ning Zhang, Los Angeles, CA (US);

Jia Li, Marina Del Rey, CA (US);

Assignee:

Snap Inc., Santa Monica, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/246 (2017.01); G06T 7/33 (2017.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06T 7/40 (2017.01);
U.S. Cl.
CPC ...
G06T 7/248 (2017.01); G06T 7/33 (2017.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06T 7/40 (2013.01); G06T 2207/20084 (2013.01);
Abstract

Dense feature scale detection can be implemented using multiple convolutional neural networks trained on scale data to more accurately and efficiently match pixels between images. An input image can be used to generate multiple scaled images. The multiple scaled images are input into a feature net, which outputs feature data for the multiple scaled images. An attention net is used to generate an attention map from the input image. The attention map assigns emphasis as a soft distribution to different scales based on texture analysis. The feature data and the attention data can be combined through a multiplication process and then summed to generate dense features for comparison.


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