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. 31, 2023

Filed:

Dec. 10, 2020
Applicant:

Amazon Technologies, Inc., Seattle, WA (US);

Inventors:

Aleix Margarit Martinez, Seattle, WA (US);

Raghu Deep Gadde, Bellevue, WA (US);

Qianli Feng, Columbus, OH (US);

Alexandru Indrei, Bothell, WA (US);

Gerard Gjonej, Bellevue, WA (US);

Assignee:

AMAZON TECHNOLOGIES, INC., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 11/00 (2006.01); G06T 7/11 (2017.01); G06K 9/62 (2022.01); G06T 7/70 (2017.01);
U.S. Cl.
CPC ...
G06T 11/00 (2013.01); G06K 9/6217 (2013.01); G06K 9/6267 (2013.01); G06T 7/11 (2017.01); G06T 7/70 (2017.01); G06T 2207/10016 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20132 (2013.01);
Abstract

Techniques are generally described for generation of photorealistic synthetic image data. A generator network generates first synthetic image data. A first class of image data represented by a first portion of the first synthetic image data is detected and the first portion is sent to a first discriminator network. The first discriminator network generates a prediction of whether the first portion of the first synthetic image data is synthetically generated. A second class of image data represented by a second portion of the first synthetic image data is detected and the second portion is sent to a second discriminator network. The second discriminator network generates a prediction of whether the second portion of the first synthetic image data is synthetically generated. The generator network is updated based on the predictions of the discriminators.


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