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1.发明申请公开(公告)号：US20250124544A1
公开(公告)日：2025-04-17
申请号：US18487764
申请日：2023-10-16
Applicant: ADOBE INC.
Inventor： Taesung Park , Qing Liu , Zhe Lin , Sohrab Amirghodsi , Elya Shechtman
Abstract: Systems and methods for upsampling low-resolution content within a high-resolution image include obtaining a composite image and a mask. The composite image includes a high-resolution region and a low-resolution region. An upsampling network identifies the low-resolution region of the composite image based on the mask and generates an upsampled composite image based on the composite image and the mask. The upsampled composite image comprises higher frequency details in the low-resolution region than the composite image.
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公开(公告)号：US20240338869A1
公开(公告)日：2024-10-10
申请号：US18474536
申请日：2023-09-26
Applicant: ADOBE INC.
Inventor： Yuqian Zhou , Krishna Kumar Singh , Zhifei Zhang , Difan Liu , Zhe Lin , Jianming Zhang , Qing Liu , Jingwan Lu , Elya Shechtman , Sohrab Amirghodsi , Connelly Stuart Barnes
IPC: G06T11/60
CPC classification number: G06T11/60
Abstract: An image processing system obtains an input image (e.g., a user provided image, etc.) and a mask indicating an edit region of the image. A user selects an image editing mode for an image generation network from a plurality of image editing modes. The image generation network generates an output image using the input image, the mask, and the image editing mode.
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公开(公告)号：US20240281978A1
公开(公告)日：2024-08-22
申请号：US18170336
申请日：2023-02-16
Applicant: Adobe Inc.
Inventor： Jingyuan Liu , Qing Liu , Jimei Yang , Yuhong Wu , Su Chen
CPC classification number: G06T7/11 , G06V10/267 , G06V10/7715 , G06V10/82 , G06V20/70 , G06T2207/20021 , G06T2207/20084
Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating segmentation masks for a digital visual media item. In particular, in one or more embodiments, the disclosed systems generate, utilizing a neural network encoder, high-level features of a digital visual media item. Further, the disclosed systems generate, utilizing the neural network encoder, low-level features of the digital visual media item. In some implementations, the disclosed systems generate, utilizing a neural network decoder, an initial segmentation mask of the digital visual media item from the low-level features. Moreover, the disclosed systems generate, utilizing the neural network decoder, a refined segmentation mask of the digital visual media item from the initial segmentation mask and the high-level features.
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公开(公告)号：US20240169500A1
公开(公告)日：2024-05-23
申请号：US18058027
申请日：2022-11-22
Applicant: ADOBE INC.
Inventor： Haitian Zheng , Zhe Lin , Jianming Zhang , Connelly Stuart Barnes , Elya Shechtman , Jingwan Lu , Qing Liu , Sohrab Amirghodsi , Yuqian Zhou , Scott Cohen
IPC: G06T5/00
CPC classification number: G06T5/005 , G06T5/003 , G06T2207/20081 , G06T2207/20104
Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure receive an image comprising a first region that includes content and a second region to be inpainted. Noise is then added to the image to obtain a noisy image, and a plurality of intermediate output images are generated based on the noisy image using a diffusion model trained using a perceptual loss. The intermediate output images predict a final output image based on a corresponding intermediate noise level of the diffusion model. The diffusion model then generates the final output image based on the intermediate output image. The final output image includes inpainted content in the second region that is consistent with the content in the first region.
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5.发明公开公开(公告)号：US20240135514A1
公开(公告)日：2024-04-25
申请号：US18460365
申请日：2023-09-01
Applicant: Adobe Inc.
Inventor： Daniil Pakhomov , Qing Liu , Zhihong Ding , Scott Cohen , Zhe Lin , Jianming Zhang , Zhifei Zhang , Ohiremen Dibua , Mariette Souppe , Krishna Kumar Singh , Jonathan Brandt
IPC: G06T5/00 , G06F3/04845 , G06T7/11 , G06T7/194 , G06T7/70
CPC classification number: G06T5/005 , G06F3/04845 , G06T5/002 , G06T7/11 , G06T7/194 , G06T7/70 , G06T2200/24 , G06T2207/20021 , G06T2207/20084 , G06T2207/20092
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via multi-layered scene completion techniques facilitated by artificial intelligence. For instance, in some embodiments, the disclosed systems receive a digital image portraying a first object and a second object against a background, where the first object occludes a portion of the second object. Additionally, the disclosed systems pre-process the digital image to generate a first content fill for the portion of the second object occluded by the first object and a second content fill for a portion of the background occluded by the second object. After pre-processing, the disclosed systems detect one or more user interactions to move or delete the first object from the digital image. The disclosed systems further modify the digital image by moving or deleting the first object and exposing the first content fill for the portion of the second object.
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Patent Agency Ranking
6.发明公开公开(公告)号：US20240127412A1
公开(公告)日：2024-04-18
申请号：US17937708
申请日：2022-10-03
Applicant: Adobe Inc.
Inventor： Zhe Lin , Haitian Zheng , Elya Shechtman , Jianming Zhang , Jingwan Lu , Ning Xu , Qing Liu , Scott Cohen , Sohrab Amirghodsi
CPC classification number: G06T5/005 , G06T7/11 , G06T2207/20084 , G06T2207/20092
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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公开(公告)号：US20250086849A1
公开(公告)日：2025-03-13
申请号：US18463333
申请日：2023-09-08
Applicant: ADOBE INC.
Inventor： Yu Zeng , Zhe Lin , Jianming Zhang , Qing Liu , Jason Wen Yong Kuen , John Philip Collomosse
IPC: G06T11/00 , G06F40/295 , G06F40/30 , G06V10/774 , G06V10/776 , G06V20/70
Abstract: Embodiments of the present disclosure include obtaining a text prompt describing an element, layout information indicating a target region for the element, and a precision level corresponding to the element. Some embodiments generate a text feature pyramid based on the text prompt, the layout information, and the precision level, wherein the text feature pyramid comprises a plurality of text feature maps at a plurality of scales, respectively. Then, an image is generated based on the text feature pyramid. In some cases, the image includes an object corresponding to the element of the text prompt at the target region. Additionally, a shape of the object corresponds to a shape of the target region based on the precision level.
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8.发明公开公开(公告)号：US20240135509A1
公开(公告)日：2024-04-25
申请号：US18190500
申请日：2023-03-27
Applicant: Adobe Inc.
Inventor： Qing Liu , Jianming Zhang , Krishna Kumar Singh , Scott Cohen , Zhe Lin
CPC classification number: G06T5/005 , G06T5/002 , G06T7/11 , G06T11/60 , G06V10/764 , G06V10/82 , G06V20/70 , G06T2200/24 , G06T2207/20021 , G06T2207/20084
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that modify digital images via scene-based editing using image understanding facilitated by artificial intelligence. For example, in one or more embodiments the disclosed systems utilize generative machine learning models to create modified digital images portraying human subjects. In particular, the disclosed systems generate modified digital images by performing infill modifications to complete a digital image or human inpainting for portions of a digital image that portrays a human. Moreover, in some embodiments, the disclosed systems perform reposing of subjects portrayed within a digital image to generate modified digital images. In addition, the disclosed systems in some embodiments perform facial expression transfer and facial expression animations to generate modified digital images or animations.
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9.发明公开公开(公告)号：US20240127411A1
公开(公告)日：2024-04-18
申请号：US17937706
申请日：2022-10-03
Applicant: Adobe Inc.
Inventor： Zhe Lin , Haitian Zheng , Elya Shechtman , Jianming Zhang , Jingwan Lu , Ning Xu , Qing Liu , Scott Cohen , Sohrab Amirghodsi
CPC classification number: G06T5/005 , G06T7/11 , G06T2200/24 , G06T2207/20081 , G06T2207/20084
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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公开(公告)号：US20240127410A1
公开(公告)日：2024-04-18
申请号：US17937695
申请日：2022-10-03
Applicant: Adobe Inc.
Inventor： Zhe Lin , Haitian Zheng , Elya Shechtman , Jianming Zhang , Jingwan Lu , Ning Xu , Qing Liu , Scott Cohen , Sohrab Amirghodsi
CPC classification number: G06T5/005 , G06T7/11 , G06T2207/20084
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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