Invention Grant
- Patent Title: Synthesizing digital images utilizing image-guided model inversion of an image classifier
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Application No.: US17178681Application Date: 2021-02-18
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Publication No.: US11842468B2Publication Date: 2023-12-12
- Inventor: Pei Wang , Yijun Li , Jingwan Lu , Krishna Kumar Singh
- 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: G06K9/00
- IPC: G06K9/00 ; G06T5/50 ; G06N3/04 ; G06V10/75 ; G06F18/22 ; G06F18/24

Abstract:
This disclosure describes methods, non-transitory computer readable storage media, and systems that utilize image-guided model inversion of an image classifier with a discriminator. The disclosed systems utilize a neural network image classifier to encode features of an initial image and a target image. The disclosed system also reduces a feature distance between the features of the initial image and the features of the target image at a plurality of layers of the neural network image classifier by utilizing a feature distance regularizer. Additionally, the disclosed system reduces a patch difference between image patches of the initial image and image patches of the target image by utilizing a patch-based discriminator with a patch consistency regularizer. The disclosed system then generates a synthesized digital image based on the constrained feature set and constrained image patches of the initial image.
Public/Granted literature
- US20220261972A1 SYNTHESIZING DIGITAL IMAGES UTILIZING IMAGE-GUIDED MODEL INVERSION OF AN IMAGE CLASSIFIER Public/Granted day:2022-08-18
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