Invention Grant
- Patent Title: Utilizing a two-stream encoder neural network to generate composite digital images
-
Application No.: US17483280Application Date: 2021-09-23
-
Publication No.: US11568544B2Publication Date: 2023-01-31
- Inventor: Zhe Lin , Jianming Zhang , He Zhang , Federico Perazzi
- 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 Preece PLLC
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06T7/10 ; G06N3/04 ; G06N3/08 ; G06T11/60

Abstract:
The present disclosure relates to utilizing a neural network having a two-stream encoder architecture to accurately generate composite digital images that realistically portray a foreground object from one digital image against a scene from another digital image. For example, the disclosed systems can utilize a foreground encoder of the neural network to identify features from a foreground image and further utilize a background encoder to identify features from a background image. The disclosed systems can then utilize a decoder to fuse the features together and generate a composite digital image. The disclosed systems can train the neural network utilizing an easy-to-hard data augmentation scheme implemented via self-teaching. The disclosed systems can further incorporate the neural network within an end-to-end framework for automation of the image composition process.
Public/Granted literature
- US20220012885A1 UTILIZING A TWO-STREAM ENCODER NEURAL NETWORK TO GENERATE COMPOSITE DIGITAL IMAGES Public/Granted day:2022-01-13
Information query