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:
Jun. 18, 2024

Filed:

Dec. 29, 2021
Applicant:

Beihang University, Beijing, CN;

Inventors:

Feng Lu, Beijing, CN;

Yunfei Liu, Beijing, CN;

Assignee:

Beihang University, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 3/4046 (2024.01); G06T 5/20 (2006.01); G06T 5/70 (2024.01); G06V 10/20 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/80 (2022.01); G06V 20/64 (2022.01);
U.S. Cl.
CPC ...
G06T 3/4046 (2013.01); G06T 5/20 (2013.01); G06T 5/70 (2024.01); G06V 10/255 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/806 (2022.01); G06V 20/64 (2022.01);
Abstract

The embodiments of this disclosure disclose an unsupervised image-to-image translation method. A specific implementation of this method comprises: obtaining an initial image, and zooming the initial image to a specific size; performing spatial feature extraction on the initial image to obtain feature information; inputting the feature information to a style-content separation module to obtain content feature information and style feature information; generating reference style feature information of a reference image in response to obtaining the reference image, and setting the reference style feature information as a Gaussian noise in response to not obtaining the reference image; inputting the content feature information and the reference style feature information into a generator to obtain a target image; and zooming the target image to obtain a final target image. This implementation can be applied to a variety of different high-level visual tasks, and improve the expandability of the whole system.


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