Invention Grant
- Patent Title: Iteratively applying neural networks to automatically identify pixels of salient objects portrayed in digital images
-
Application No.: US15967928Application Date: 2018-05-01
-
Publication No.: US11244195B2Publication Date: 2022-02-08
- Inventor: I-Ming Pao , Zhe Lin , Sarah Stuckey , Jianming Zhang , Betty Leong
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Keller Jolley Preece
- Main IPC: G06K9/46
- IPC: G06K9/46 ; G06K9/62 ; G06T3/40

Abstract:
The present disclosure relates to systems, method, and computer readable media that iteratively apply a neural network to a digital image at a reduced resolution to automatically identify pixels of salient objects portrayed within the digital image. For example, the disclosed systems can generate a reduced-resolution digital image from an input digital image and apply a neural network to identify a region corresponding to a salient object. The disclosed systems can then iteratively apply the neural network to additional reduced-resolution digital images (based on the identified region) to generate one or more reduced-resolution segmentation maps that roughly indicate pixels of the salient object. In addition, the systems described herein can perform post-processing based on the reduced-resolution segmentation map(s) and the input digital image to accurately determine pixels that correspond to the salient object.
Public/Granted literature
Information query