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:
Nov. 07, 2023

Filed:

Apr. 26, 2021
Applicant:

Adobe Inc., San Jose, CA (US);

Inventors:

Zhaowen Wang, San Jose, CA (US);

Hailin Jin, San Jose, CA (US);

Yang Liu, Cambridge, GB;

Assignee:

Adobe Inc., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/62 (2022.01); G06V 30/148 (2022.01); G06F 18/214 (2023.01); G06V 10/764 (2022.01);
U.S. Cl.
CPC ...
G06V 20/62 (2022.01); G06F 18/214 (2023.01); G06V 10/764 (2022.01); G06V 20/63 (2022.01); G06V 30/153 (2022.01); G06V 2201/01 (2022.01);
Abstract

In implementations of recognizing text in images, text recognition systems are trained using noisy images that have nuisance factors applied, and corresponding clean images (e.g., without nuisance factors). Clean images serve as supervision at both feature and pixel levels, so that text recognition systems are trained to be feature invariant (e.g., by requiring features extracted from a noisy image to match features extracted from a clean image), and feature complete (e.g., by requiring that features extracted from a noisy image be sufficient to generate a clean image). Accordingly, text recognition systems generalize to text not included in training images, and are robust to nuisance factors. Furthermore, since clean images are provided as supervision at feature and pixel levels, training requires fewer training images than text recognition systems that are not trained with a supervisory clean image, thus saving time and resources.


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