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公开(公告)号：US20240320789A1
公开(公告)日：2024-09-26
申请号：US18585957
申请日：2024-02-23
Applicant: ADOBE INC.
Inventor： Tobias Hinz , Taesung Park , Jingwan Lu , Elya Shechtman , Richard Zhang , Oliver Wang
IPC: G06T3/4053 , G06T3/4046 , G06T11/00
CPC classification number: G06T3/4053 , G06T3/4046 , G06T11/00
Abstract: A method, non-transitory computer readable medium, apparatus, and system for image generation include obtaining an input image having a first resolution, where the input image includes random noise, and generating a low-resolution image based on the input image, where the low-resolution image has the first resolution. The method, non-transitory computer readable medium, apparatus, and system further include generating a high-resolution image based on the low-resolution image, where the high-resolution image has a second resolution that is greater than the first resolution.
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公开(公告)号：US20240320873A1
公开(公告)日：2024-09-26
申请号：US18439036
申请日：2024-02-12
Applicant: ADOBE INC.
Inventor： Tobias Hinz , Ali Aminian , Hao Tan , Kushal Kafle , Oliver Wang , Jingwan Lu
IPC: G06T11/00
CPC classification number: G06T11/00 , G06T2211/441
Abstract: A method, apparatus, non-transitory computer readable medium, and system for image generation include obtaining a text prompt and encoding, using a text encoder jointly trained with an image generation model, the text prompt to obtain a text embedding. Some embodiments generate, using the image generation model, a synthetic image based on the text embedding.
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3.发明公开公开(公告)号：US20240135513A1
公开(公告)日：2024-04-25
申请号：US18190654
申请日：2023-03-27
Applicant: Adobe Inc.
Inventor： Krishna Kumar Singh , Yijun Li , Jingwan Lu , Duygu Ceylan Aksit , Yangtuanfeng Wang , Jimei Yang , Tobias Hinz
CPC classification number: G06T5/005 , G06T3/0093 , G06T7/40 , G06T7/70 , G06V10/44 , G06V10/771 , G06V10/806 , G06V10/82 , G06T2207/30196
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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公开(公告)号：US20230360376A1
公开(公告)日：2023-11-09
申请号：US17744995
申请日：2022-05-16
Applicant: Adobe Inc.
Inventor： Tobias Hinz , Taesung Park , Richard Zhang , Matthew David Fisher , Difan Liu , Evangelos Kalogerakis
IPC: G06V10/774 , G06V10/22 , G06T3/40
CPC classification number: G06V10/7753 , G06V10/235 , G06T3/4046
Abstract: Semantic fill techniques are described that support generating fill and editing images from semantic inputs. A user input, for example, is received by a semantic fill system that indicates a selection of a first region of a digital image and a corresponding semantic label. The user input is utilized by the semantic fill system to generate a guidance attention map of the digital image. The semantic fill system leverages the guidance attention map to generate a sparse attention map of a second region of the digital image. A semantic fill of pixels is generated for the first region based on the semantic label and the sparse attention map. The edited digital image is displayed in a user interface.
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公开(公告)号：US20240265505A1
公开(公告)日：2024-08-08
申请号：US18165141
申请日：2023-02-06
Applicant: ADOBE INC.
Inventor： Cusuh Ham , Tobias Hinz , Jingwan Lu , Krishna Kumar Singh , Zhifei Zhang
IPC: G06T5/00
CPC classification number: G06T5/70 , G06T2207/20081 , G06T2207/20084
Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure obtain a noise image and guidance information for generating an image. A diffusion model generates an intermediate noise prediction for the image based on the noise image. A conditioning network generates noise modulation parameters. The intermediate noise prediction and the noise modulation parameters are combined to obtain a modified intermediate noise prediction. The diffusion model generates the image based on the modified intermediate noise prediction, wherein the image depicts a scene based on the guidance information.
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Patent Agency Ranking
公开(公告)号：US20240135572A1
公开(公告)日：2024-04-25
申请号：US18190636
申请日：2023-03-27
Applicant: Adobe Inc.
Inventor： Krishna Kumar Singh , Yijun Li , Jingwan Lu , Duygu Ceylan Aksit , Yangtuanfeng Wang , Jimei Yang , Tobias Hinz
CPC classification number: G06T7/70 , G06T7/40 , G06V10/44 , G06V10/771 , G06V10/806 , G06V10/82 , G06T2207/20081 , G06T2207/30196
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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公开(公告)号：US12260530B2
公开(公告)日：2025-03-25
申请号：US18190544
申请日：2023-03-27
Applicant: Adobe Inc.
Inventor： Krishna Kumar Singh , Yijun Li , Jingwan Lu , Duygu Ceylan Aksit , Yangtuanfeng Wang , Jimei Yang , Tobias Hinz , Qing Liu , Jianming Zhang , Zhe Lin
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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8.发明授权公开(公告)号：US12211178B2
公开(公告)日：2025-01-28
申请号：US17660090
申请日：2022-04-21
Applicant: Adobe Inc.
Inventor： Tobias Hinz , Shabnam Ghadar , Richard Zhang , Ratheesh Kalarot , Jingwan Lu , Elya Shechtman
Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for combining digital images. In particular, in one or more embodiments, the disclosed systems combine latent codes of a source digital image and a target digital image utilizing a blending network to determine a combined latent encoding and generate a combined digital image from the combined latent encoding utilizing a generative neural network. In some embodiments, the disclosed systems determine an intersection face mask between the source digital image and the combined digital image utilizing a face segmentation network and combine the source digital image and the combined digital image utilizing the intersection face mask to generate a blended digital image.
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公开(公告)号：US20240320872A1
公开(公告)日：2024-09-26
申请号：US18426763
申请日：2024-01-30
Applicant: ADOBE INC.
Inventor： Tobias Hinz , Venkata Naveen Kumar Yadav Marri , Midhun Harikumar , Ajinkya Gorakhnath Kale , Zhe Lin , Oliver Wang , Jingwan Lu
IPC: G06T11/00 , G06F40/284 , G06F40/40
CPC classification number: G06T11/00 , G06F40/284 , G06F40/40 , G06T2207/20081 , G06T2207/20084
Abstract: A method, apparatus, non-transitory computer readable medium, and system for image generation include obtaining a text embedding of a text prompt and an image embedding of an image prompt. Some embodiments map the text embedding into a joint embedding space to obtain a joint text embedding and map the image embedding into the joint embedding space to obtain a joint image embedding. Some embodiments generate a synthetic image based on the joint text embedding and the joint image embedding.
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10.发明公开公开(公告)号：US20240135512A1
公开(公告)日：2024-04-25
申请号：US18190556
申请日：2023-03-27
Applicant: Adobe Inc.
Inventor： Krishna Kumar Singh , Yijun Li , Jingwan Lu , Duygu Ceylan Aksit , Yangtuanfeng Wang , Jimei Yang , Tobias Hinz , Qing Liu , Jianming Zhang , Zhe Lin
CPC classification number: G06T5/005 , G06T7/11 , G06V10/82 , G06V40/10 , G06T2207/20021 , G06T2207/20084 , G06T2207/20212 , G06T2207/30196
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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