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公开(公告)号：US20240331214A1
公开(公告)日：2024-10-03
申请号：US18610861
申请日：2024-03-20
申请人： ADOBE INC.
发明人： Yuqian Zhou , Elya Shechtman , Zhe Lin , Krishna Kumar Singh , Jingwan Lu , Connelly Stuart Barnes , Sohrab Amirghodsi
IPC分类号： G06T11/00 , G06T3/4046 , G06T5/30
CPC分类号： G06T11/00 , G06T3/4046 , G06T5/30 , G06T2200/24 , G06T2207/20084
摘要： Systems and methods for image processing (e.g., image extension or image uncropping) using neural networks are described. One or more aspects include obtaining an image (e.g., a source image, a user provided image, etc.) having an initial aspect ratio, and identifying a target aspect ratio (e.g., via user input) that is different from the initial aspect ratio. The image may be positioned in an image frame having the target aspect ratio, where the image frame includes an image region containing the image and one or more extended regions outside the boundaries of the image. An extended image may be generated (e.g., using a generative neural network), where the extended image includes the image in the image region as well as generated image portions in the extended regions and the one or more generated image portions comprise an extension of a scene element depicted in the image.
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公开(公告)号：US12086965B2
公开(公告)日：2024-09-10
申请号：US17520361
申请日：2021-11-05
申请人： Adobe Inc.
发明人： Yunhan Zhao , Connelly Barnes , Yuqian Zhou , Sohrab Amirghodsi , Elya Shechtman
CPC分类号： G06T5/77 , G06T3/18 , G06T3/4046 , G06T5/50 , G06T7/30 , G06T7/50 , G06T7/90 , G06T2207/20084 , G06T2207/20221
摘要： The present disclosure relates to systems, methods, and non-transitory computer-readable media for accurately restoring missing pixels within a hole region of a target image utilizing multi-image inpainting techniques based on incorporating geometric depth information. For example, in various implementations, the disclosed systems utilize a depth prediction of a source image as well as camera relative pose parameters. Additionally, in some implementations, the disclosed systems jointly optimize the depth rescaling and camera pose parameters before generating the reprojected image to further increase the accuracy of the reprojected image. Further, in various implementations, the disclosed systems utilize the reprojected image in connection with a content-aware fill model to generate a refined composite image that includes the target image having a hole, where the hole is filled in based on the reprojected image of the source image.
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3.发明公开公开(公告)号：US20240127452A1
公开(公告)日：2024-04-18
申请号：US17937680
申请日：2022-10-03
申请人： Adobe Inc.
发明人： Zhe Lin , Haitian Zheng , Elya Shechtman , Jianming Zhang , Jingwan Lu , Ning Xu , Qing Liu , Scott Cohen , Sohrab Amirghodsi
IPC分类号： G06T7/11
CPC分类号： G06T7/11 , G06T2207/20081 , G06T2207/20084 , G06T2207/20132
摘要： 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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4.发明公开公开(公告)号：US20230259587A1
公开(公告)日：2023-08-17
申请号：US17650967
申请日：2022-02-14
申请人： Adobe Inc.
发明人： Zhe Lin , Haitian Zheng , Jingwan Lu , Scott Cohen , Jianming Zhang , Ning Xu , Elya Shechtman , Connelly Barnes , Sohrab Amirghodsi
CPC分类号： G06K9/6257 , G06T5/005 , G06T7/11 , G06N3/08 , G06T2207/20084 , G06T2207/20081
摘要： The present disclosure relates to systems, methods, and non-transitory computer readable media for training a generative inpainting neural network to accurately generate inpainted digital images via object-aware training and/or masked regularization. For example, the disclosed systems utilize an object-aware training technique to learn parameters for a generative inpainting neural network based on masking individual object instances depicted within sample digital images of a training dataset. In some embodiments, the disclosed systems also (or alternatively) utilize a masked regularization technique as part of training to prevent overfitting by penalizing a discriminator neural network utilizing a regularization term that is based on an object mask. In certain cases, the disclosed systems further generate an inpainted digital image utilizing a trained generative inpainting model with parameters learned via the object-aware training and/or the masked regularization
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公开(公告)号：US20230145498A1
公开(公告)日：2023-05-11
申请号：US17520361
申请日：2021-11-05
申请人： Adobe Inc.
发明人： Yunhan Zhao , Connelly Barnes , Yuqian Zhou , Sohrab Amirghodsi , Elya Shechtman
CPC分类号： G06T5/005 , G06T3/0093 , G06T3/4046 , G06T5/50 , G06T7/30 , G06T7/50 , G06T7/90 , G06T2207/20084 , G06T2207/20221
摘要： The present disclosure relates to systems, methods, and non-transitory computer-readable media for accurately restoring missing pixels within a hole region of a target image utilizing multi-image inpainting techniques based on incorporating geometric depth information. For example, in various implementations, the disclosed systems utilize a depth prediction of a source image as well as camera relative pose parameters. Additionally, in some implementations, the disclosed systems jointly optimize the depth rescaling and camera pose parameters before generating the reprojected image to further increase the accuracy of the reprojected image. Further, in various implementations, the disclosed systems utilize the reprojected image in connection with a content-aware fill model to generate a refined composite image that includes the target image having a hole, where the hole is filled in based on the reprojected image of the source image.
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公开(公告)号：US11449974B2
公开(公告)日：2022-09-20
申请号：US16678132
申请日：2019-11-08
申请人： Adobe Inc.
摘要： The present disclosure relates to systems, methods, and non-transitory computer readable media for generating modified digital images by utilizing a patch match algorithm to generate nearest neighbor fields for a second digital image based on a nearest neighbor field associated with a first digital image. For example, the disclosed systems can identify a nearest neighbor field associated with a first digital image of a first resolution. Based on the nearest neighbor field of the first digital image, the disclosed systems can utilize a patch match algorithm to generate a nearest neighbor field for a second digital image of a second resolution larger than the first resolution. The disclosed systems can further generate a modified digital image by filling a target region of the second digital image utilizing the generated nearest neighbor field.
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公开(公告)号：US20220156893A1
公开(公告)日：2022-05-19
申请号：US17098055
申请日：2020-11-13
申请人： ADOBE INC.
摘要： Various disclosed embodiments are directed to inpainting one or more portions of a target image based on merging (or selecting) one or more portions of a warped image with (or from) one or more portions of an inpainting candidate (e.g., via a learning model). This, among other functionality described herein, resolves the inaccuracies of existing image inpainting technologies.
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公开(公告)号：US10719913B2
公开(公告)日：2020-07-21
申请号：US16160855
申请日：2018-10-15
申请人： ADOBE INC.
摘要： Embodiments of the present invention provide systems, methods, and computer storage media directed at image synthesis utilizing sampling of patch correspondence information between iterations at different scales. A patch synthesis technique can be performed to synthesize a target region at a first image scale based on portions of a source region that are identified by the patch synthesis technique. The image can then be sampled to generate an image at a second image scale. The sampling can include generating patch correspondence information for the image at the second image scale. Invalid patch assignments in the patch correspondence information at the second image scale can then be identified, and valid patches can be assigned to the pixels having invalid patch assignments. Other embodiments may be described and/or claimed.
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公开(公告)号：US20190287225A1
公开(公告)日：2019-09-19
申请号：US15921457
申请日：2018-03-14
申请人： ADOBE INC.
摘要： Embodiments of the present invention provide systems, methods, and computer storage media for improved patch validity testing for patch-based synthesis applications using similarity transforms. The improved patch validity tests are used to validate (or invalidate) candidate patches as valid patches falling within a sampling region of a source image. The improved patch validity tests include a hole dilation test for patch validity, a no-dilation test for patch invalidity, and a comprehensive pixel test for patch invalidity. A fringe test for range invalidity can be used to identify pixels with an invalid range and invalidate corresponding candidate patches. The fringe test for range invalidity can be performed as a precursor to any or all of the improved patch validity tests. In this manner, validated candidate patches are used to automatically reconstruct a target image.
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10.发明公开公开(公告)号：US20240331114A1
公开(公告)日：2024-10-03
申请号：US18743497
申请日：2024-06-14
申请人： Adobe Inc.
摘要： The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately generating inpainted digital images utilizing a guided inpainting model guided by both plane panoptic segmentation and plane grouping. For example, the disclosed systems utilize a guided inpainting model to fill holes of missing pixels of a digital image as informed or guided by an appearance guide and a geometric guide. Specifically, the disclosed systems generate an appearance guide utilizing plane panoptic segmentation and generate a geometric guide by grouping plane panoptic segments. In some embodiments, the disclosed systems generate a modified digital image by implementing an inpainting model guided by both the appearance guide (e.g., a plane panoptic segmentation map) and the geometric guide (e.g., a plane grouping map).
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