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:
Oct. 29, 2019

Filed:

Oct. 31, 2017
Applicant:

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

Inventors:

Xin Lu, Mountain View, CA (US);

Zhe Lin, Fremont, CA (US);

Xiaohui Shen, San Jose, CA (US);

Jimei Yang, Merced, CA (US);

Jianming Zhang, Campbell, CA (US);

Jen-Chan Jeff Chien, Saratoga, CA (US);

Chenxi Liu, Baltimore, MD (US);

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/66 (2006.01); G06K 9/46 (2006.01); G06T 7/194 (2017.01);
U.S. Cl.
CPC ...
G06K 9/66 (2013.01); G06K 9/4628 (2013.01); G06K 9/4671 (2013.01); G06T 7/194 (2017.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01);
Abstract

Systems, methods, and non-transitory computer-readable media are disclosed for segmenting objects in digital visual media utilizing one or more salient content neural networks. In particular, in one or more embodiments, the disclosed systems and methods train one or more salient content neural networks to efficiently identify foreground pixels in digital visual media. Moreover, in one or more embodiments, the disclosed systems and methods provide a trained salient content neural network to a mobile device, allowing the mobile device to directly select salient objects in digital visual media utilizing a trained neural network. Furthermore, in one or more embodiments, the disclosed systems and methods train and provide multiple salient content neural networks, such that mobile devices can identify objects in real-time digital visual media feeds (utilizing a first salient content neural network) and identify objects in static digital images (utilizing a second salient content neural network).


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