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. 25, 2026

Filed:

Jun. 11, 2024
Applicant:

Roblox Corporation, San Mateo, CA (US);

Inventors:

Nicolas Thiebaut, San Francisco, CA (US);

Dao Le, San Jose, CA (US);

Xiao Yu, San Mateo, CA (US);

Kyle Joseph Spence, Redwood City, CA (US);

Nameer Hirschkind, San Francisco, CA (US);

Assignee:

Roblox Corporation, San Mateo, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 11/60 (2026.01); G06F 40/51 (2020.01); G06F 40/58 (2020.01); G06T 11/23 (2026.01); G06V 30/148 (2022.01); G06V 30/19 (2022.01);
U.S. Cl.
CPC ...
G06T 11/60 (2013.01); G06F 40/51 (2020.01); G06F 40/58 (2020.01); G06T 11/23 (2026.01); G06V 30/153 (2022.01); G06V 30/19147 (2022.01); G06V 30/1916 (2022.01); G06T 2210/12 (2013.01);
Abstract

Some implementations relate to translating text within images in a virtual environment while preserving the original style and visual characteristics of the text. In some implementations, the method includes obtaining an original image that includes text in a source language; recognizing content of the text and generating translated text in a target language; determining a text region of the text in the original image; determining a style encoding for the text; generating a masked version and noisy version of the original image; providing the noisy version, masked version, and text region as direct inputs to a pre-trained diffusion model; providing the translated text and the style encoding as conditioning inputs to the diffusion model; and obtaining an output image including the translated text, where a visual style of the translated text in the output image is the same as the visual style of the text in the original image.


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