Invention Grant
- Patent Title: Diverse image inpainting using contrastive learning
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Application No.: US17725818Application Date: 2022-04-21
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Publication No.: US12272031B2Publication Date: 2025-04-08
- Inventor: Krishna Kumar Singh , Yuheng Li , Yijun Li , Jingwan Lu , Elya Shechtman
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: FIG. 1 Patents
- Main IPC: G06T5/70
- IPC: G06T5/70 ; G06N3/045 ; G06T5/77 ; G06V10/74 ; G06V10/82

Abstract:
An image inpainting system is described that receives an input image that includes a masked region. From the input image, the image inpainting system generates a synthesized image that depicts an object in the masked region by selecting a first code that represents a known factor characterizing a visual appearance of the object and a second code that represents an unknown factor characterizing the visual appearance of the object apart from the known factor in latent space. The input image, the first code, and the second code are provided as input to a generative adversarial network that is trained to generate the synthesized image using contrastive losses. Different synthesized images are generated from the same input image using different combinations of first and second codes, and the synthesized images are output for display.
Public/Granted literature
- US20230342884A1 Diverse Image Inpainting Using Contrastive Learning Public/Granted day:2023-10-26
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