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公开(公告)号：US20210382936A1
公开(公告)日：2021-12-09
申请号：US16897008
申请日：2020-06-09
Applicant: ADOBE INC.
Inventor： Devavrat Tomar , Aliakbar Darabi
Abstract: Various disclosed embodiments are directed to classify or determining an image style of a target image according to a consumer application based on determining a similarity score between the image style of a target image and one or more other predetermined image styles of the consumer application. Various disclosed embodiments can resolve image style transfer destructiveness functionality by making various layers of predetermined image styles modifiable. Further various embodiments resolve tedious manual user input requirements and reduce computing resource consumption, among other things.
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公开(公告)号：US10915991B2
公开(公告)日：2021-02-09
申请号：US16509263
申请日：2019-07-11
Applicant: ADOBE INC.
Inventor： Sylvain Paris , Sohrab Amirghodsi , Aliakbar Darabi , Elya Shechtman
Abstract: Embodiments described herein are directed to methods and systems for facilitating control of smoothness of transitions between images. In embodiments, a difference of color values of pixels between a foreground image and the background image are identified along a boundary associated with a location at which to paste the foreground image relative to the background image. Thereafter, recursive down sampling of a region of pixels within the boundary by a sampling factor is performed to produce a plurality of down sampled images having color difference indicators associated with each pixel of the down sampled images. Such color difference indicators indicate whether a difference of color value exists for the corresponding pixel. To effectuate a seamless transition, the color difference indicators are normalized in association with each recursively down sampled image.
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公开(公告)号：US12271996B2
公开(公告)日：2025-04-08
申请号：US18166189
申请日：2023-02-08
Applicant: ADOBE INC.
Inventor： Sudeep Siddheshwar Katakol , Taesung Park , Aliakbar Darabi , Kevin Duarte , Ryan Joe Murdock
Abstract: A method for training a GAN to transfer lighting from a reference image to a source image includes: receiving the source image and the reference image; generating a lighting vector from the reference image; applying features of the source image and the lighting vector to a generative network of the GAN to create a generated image; applying features of the reference image and the lighting vector to a discriminative network of the GAN to update weights of the discriminative network; and applying features of the generated image and the lighting vector to the discriminative network to update weights of the generative network.
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公开(公告)号：US20240338870A1
公开(公告)日：2024-10-10
申请号：US18479379
申请日：2023-10-02
Applicant: ADOBE INC.
Inventor： Siddharth Iyer , David Davenport Bourgin , Sudeep Katakol , Aliakbar Darabi
IPC: G06T11/60
CPC classification number: G06T11/60 , G06T2200/24
Abstract: A method, apparatus, and non-transitory computer readable medium for image generation are described. Embodiments of the present disclosure obtain, via a user interface, an input text. The user interface also obtains a text effect prompt that describes a text effect for the input text. An image generation model generates an output image depicting the input text with the text effect described by the text effect prompt.
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公开(公告)号：US20240338829A1
公开(公告)日：2024-10-10
申请号：US18500263
申请日：2023-11-02
Applicant: ADOBE INC.
Inventor： Sudeep Katakol , Siddharth Iyer , Aliakbar Darabi
CPC classification number: G06T7/194 , G06T7/11 , G06T11/60 , G06T2207/10024 , G06T2207/20081 , G06T2207/20084 , G06T2207/20212
Abstract: Embodiments of the present disclosure include obtaining an input image and an approximate mask that approximately indicates a foreground region of the input image. Some embodiments generate an unconditional mask of the foreground region based on the input image. A conditional mask of the foreground region is generated based on the input image and the approximate mask. Then, an output image is generated based on the unconditional mask and the conditional mask. In some cases, the output image includes the foreground region of the input image.
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Patent Agency Ranking
26.发明公开公开(公告)号：US20230359325A1
公开(公告)日：2023-11-09
申请号：US17737452
申请日：2022-05-05
Applicant: Adobe Inc.
Inventor： Oliver Brdiczka , Nipun Jindal , Kushith Amerasinghe , Gabriel Boroghina , Dan-Gabriel Ghita , Cristian-Catalin Buzoiu , Arpit Mathur , Aliakbar Darabi , Alexandru Vasile Costin
IPC: G06F3/0482 , G06F16/58 , G06F16/532 , G06F16/583 , G06F3/04847
CPC classification number: G06F3/0482 , G06F16/5866 , G06F16/532 , G06F16/5846 , G06F3/04847 , G06F2203/04806
Abstract: An illustrator system accesses a multi-element document including a plurality of elements. The illustrator system selects, from the plurality of elements, a selected element. The illustrator system generates a replacement multi-element document that includes a substitute element in place of the selected element in the multi-element document, wherein the substitute element is different from the selected element. The illustrator system displays, via a user interface with the multi-element document, a preview of the replacement multi-element document providing a view of the replacement multi-element document, wherein the view of the replacement multi-element document is focused to depict the substitute element.
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公开(公告)号：US20220413881A1
公开(公告)日：2022-12-29
申请号：US17823811
申请日：2022-08-31
Applicant: Adobe Inc.
Inventor： Oliver Brdiczka , Robert Alley , Kyoung Tak Kim , Kevin Gary Smith , Aliakbar Darabi
Abstract: The present disclosure describes systems, non-transitory computer-readable media, and methods that intelligently sense digital user context across client devices applications utilizing a dynamic sensor graph framework and then utilize a persistent context store to generate flexible digital recommendations across digital applications. In one or more embodiments, the disclosed systems utilize triggers to select and activate one or more sensor graphs. These sensor graphs can include software sensors arranged according to an architecture of dependencies and subject to various constraints. The underlying architecture of dependencies and constraints in each sensor graph allows the disclosed systems to avoid race-conditions in persisting actionable user-context based signals, verify the validity of sensor output through the sensor graph, generate user-context based recommendations across multiple related applications, and accommodate a specific latency/refresh rate of context values.
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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
Applicant: Adobe Inc.
Inventor： Sohrab Amirghodsi , Aliakbar Darabi , Elya Shechtman
Abstract: 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：US20220122308A1
公开(公告)日：2022-04-21
申请号：US17468546
申请日：2021-09-07
Applicant: Adobe Inc.
Inventor： Ratheesh Kalarot , Kevin Wampler , Jingwan Lu , Jakub Fiser , Elya Shechtman , Aliakbar Darabi , Alexandru Vasile Costin
Abstract: Systems and methods seamlessly blend edited and unedited regions of an image. A computing system crops an input image around a region to be edited. The system applies an affine transformation to rotate the cropped input image. The system provides the rotated cropped input image as input to a machine learning model to generate a latent space representation of the rotated cropped input image. The system edits the latent space representation and provides the edited latent space representation to a generator neural network to generate a generated edited image. The system applies an inverse affine transformation to rotate the generated edited image and aligns an identified segment of the rotated generated edited image with an identified corresponding segment of the input image to produce an aligned rotated generated edited image. The system blends the aligned rotated generated edited image with the input image to generate an edited output image.
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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
Applicant: ADOBE INC.
Inventor： Sohrab Amirghodsi , Aliakbar Darabi , Elya Shechtman
Abstract: 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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