Invention Publication
- Patent Title: ITERATIVELY MODIFYING INPAINTED DIGITAL IMAGES BASED ON CHANGES TO PANOPTIC SEGMENTATION MAPS
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Application No.: US17937708Application Date: 2022-10-03
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Publication No.: US20240127412A1Publication Date: 2024-04-18
- Inventor: Zhe Lin , Haitian Zheng , Elya Shechtman , Jianming Zhang , Jingwan Lu , Ning Xu , Qing Liu , Scott Cohen , Sohrab Amirghodsi
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Main IPC: G06T5/00
- IPC: G06T5/00 ; G06T7/11

Abstract:
The present disclosure relates to systems, methods, and non-transitory computer readable media for panoptically guiding digital image inpainting utilizing a panoptic inpainting neural network. In some embodiments, the disclosed systems utilize a panoptic inpainting neural network to generate an inpainted digital image according to panoptic segmentation map that defines pixel regions corresponding to different panoptic labels. In some cases, the disclosed systems train a neural network utilizing a semantic discriminator that facilitates generation of digital images that are realistic while also conforming to a semantic segmentation. The disclosed systems generate and provide a panoptic inpainting interface to facilitate user interaction for inpainting digital images. In certain embodiments, the disclosed systems iteratively update an inpainted digital image based on changes to a panoptic segmentation map.
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