Invention Grant
- Patent Title: Utilizing deep learning for boundary-aware image segmentation
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Application No.: US15086590Application Date: 2016-03-31
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Publication No.: US09972092B2Publication Date: 2018-05-15
- Inventor: Zhe Lin , Yibing Song , Xin Lu , Xiaohui Shen , Jimei Yang
- Applicant: Adobe Systems Incorporated
- Applicant Address: US CA San Jose
- Assignee: ADOBE SYSTEMS INCORPORATED
- Current Assignee: ADOBE SYSTEMS INCORPORATED
- Current Assignee Address: US CA San Jose
- Agency: Keller Jolley Preece
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06T7/00 ; G06K9/66

Abstract:
Systems and methods are disclosed for segmenting a digital image to identify an object portrayed in the digital image from background pixels in the digital image. In particular, in one or more embodiments, the disclosed systems and methods use a first neural network and a second neural network to generate image information used to generate a segmentation mask that corresponds to the object portrayed in the digital image. Specifically, in one or more embodiments, the disclosed systems and methods optimize a fit between a mask boundary of the segmentation mask to edges of the object portrayed in the digital image to accurately segment the object within the digital image.
Public/Granted literature
- US20170287137A1 UTILIZING DEEP LEARNING FOR BOUNDARY-AWARE IMAGE SEGMENTATION Public/Granted day:2017-10-05
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