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公开(公告)号：US20230102055A1
公开(公告)日：2023-03-30
申请号：US18058163
申请日：2022-11-22
申请人： Adobe Inc.
发明人： Taesung Park , Richard Zhang , Oliver Wang , Junyan Zhu , Jingwan Lu , Elya Shechtman , Alexei A. Efros
摘要： The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a modified digital image from extracted spatial and global codes. For example, the disclosed systems can utilize a global and spatial autoencoder to extract spatial codes and global codes from digital images. The disclosed systems can further utilize the global and spatial autoencoder to generate a modified digital image by combining extracted spatial and global codes in various ways for various applications such as style swapping, style blending, and attribute editing.
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公开(公告)号：US11024060B1
公开(公告)日：2021-06-01
申请号：US16812669
申请日：2020-03-09
申请人： Adobe Inc.
发明人： Liqian Ma , Jingwan Lu , Zhe Lin , Connelly Barnes , Alexei A. Efros
摘要： Techniques are provided for converting a self-portrait image into a neutral-pose portrait image, including receiving a self-portrait input image, which contains at least one person who is the subject of the self-portrait. A nearest pose search selects a target neutral-pose image that closely matches or approximates the pose of the upper torso region of the subject in the self-portrait input image. Coordinate-based inpainting maps pixels from the upper torso region in the self-portrait input image to corresponding regions in the selected target neutral-pose image to produce a coarse result image. A neutral-pose composition refines the coarse result image by synthesizing details in the body region of the subject (which in some cases includes the subject's head, arms, and torso), and inpainting pixels into missing portions of the background. The refined image is composited with the original self-portrait input image to produce a neutral-pose result image.
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公开(公告)号：US20220254071A1
公开(公告)日：2022-08-11
申请号：US17163284
申请日：2021-01-29
申请人： Adobe Inc.
发明人： Utkarsh Ojha , Yijun Li , Richard Zhang , Jingwan Lu , Elya Shechtman , Alexei A. Efros
摘要： The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and efficiently modifying a generative adversarial neural network using few-shot adaptation to generate digital images corresponding to a target domain while maintaining diversity of a source domain and realism of the target domain. In particular, the disclosed systems utilize a generative adversarial neural network with parameters learned from a large source domain. The disclosed systems preserve relative similarities and differences between digital images in the source domain using a cross-domain distance consistency loss. In addition, the disclosed systems utilize an anchor-based strategy to encourage different levels or measures of realism over digital images generated from latent vectors in different regions of a latent space.
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4.发明授权公开(公告)号：US11625875B2
公开(公告)日：2023-04-11
申请号：US17091416
申请日：2020-11-06
申请人： Adobe Inc.
发明人： Taesung Park , Alexei A. Efros , Elya Shechtman , Richard Zhang , Junyan Zhu
摘要： The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly generating modified digital images utilizing a novel swapping autoencoder that incorporates scene layout. In particular, the disclosed systems can receive a scene layout map that indicates or defines locations for displaying specific digital content within a digital image. In addition, the disclosed systems can utilize the scene layout map to guide combining portions of digital image latent code to generate a modified digital image with a particular textural appearance and a particular geometric structure defined by the scene layout map. Additionally, the disclosed systems can utilize a scene layout map that defines a portion of a digital image to modify by, for instance, adding new digital content to the digital image, and can generate a modified digital image depicting the new digital content.
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5.发明申请公开(公告)号：US20220148241A1
公开(公告)日：2022-05-12
申请号：US17091416
申请日：2020-11-06
申请人： Adobe Inc.
发明人： Taesung Park , Alexei A. Efros , Elya Shechtman , Richard Zhang , Junyan Zhu
摘要： The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly generating modified digital images utilizing a novel swapping autoencoder that incorporates scene layout. In particular, the disclosed systems can receive a scene layout map that indicates or defines locations for displaying specific digital content within a digital image. In addition, the disclosed systems can utilize the scene layout map to guide combining portions of digital image latent code to generate a modified digital image with a particular textural appearance and a particular geometric structure defined by the scene layout map. Additionally, the disclosed systems can utilize a scene layout map that defines a portion of a digital image to modify by, for instance, adding new digital content to the digital image, and can generate a modified digital image depicting the new digital content.
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