Invention Grant
- Patent Title: Controlled style-content image generation based on disentangling content and style
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Application No.: US16802440Application Date: 2020-02-26
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Publication No.: US11776180B2Publication Date: 2023-10-03
- Inventor: Ning Xu , Bayram Safa Cicek , Hailin Jin , Zhaowen Wang
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Shook, Hardy & Bacon L.L.P.
- Main IPC: G06N20/20
- IPC: G06N20/20 ; G06T11/60 ; G06N3/088 ; G06T11/00 ; G06F18/214 ; G06N3/045 ; G06V10/764 ; G06V10/774 ; G06V10/82 ; G06V10/44

Abstract:
Embodiments of the present disclosure are directed towards improved models trained using unsupervised domain adaptation. In particular, a style-content adaptation system provides improved translation during unsupervised domain adaptation by controlling the alignment of conditional distributions of a model during training such that content (e.g., a class) from a target domain is correctly mapped to content (e.g., the same class) in a source domain. The style-content adaptation system improves unsupervised domain adaptation using independent control over content (e.g., related to a class) as well as style (e.g., related to a domain) to control alignment when translating between the source and target domain. This independent control over content and style can also allow for images to be generated using the style-content adaptation system that contain desired content and/or style.
Public/Granted literature
- US20210264236A1 CONTROLLED STYLE-CONTENT IMAGE GENERATION BASED ON DISENTANGLING CONTENT AND STYLE Public/Granted day:2021-08-26
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