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公开(公告)号：US11776168B2
公开(公告)日：2023-10-03
申请号：US17219391
申请日：2021-03-31
Applicant: Adobe Inc.
Inventor： Nirmal Kumawat , Zhaowen Wang , Zhifei Zhang
IPC: G06T11/00 , G06T11/60 , G06T5/00 , G06V30/148
CPC classification number: G06T11/001 , G06T5/005 , G06T11/60 , G06V30/153 , G06V30/158
Abstract: This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that extract a texture from embedded text within a digital image utilizing kerning-adjusted glyphs. For example, the disclosed systems utilize text recognition and text segmentation to identify and segment glyphs from embedded text depicted in a digital image. Subsequently, in some implementations, the disclosed systems determine optimistic kerning values between consecutive glyphs and utilize the kerning values to reduce gaps between the consecutive glyphs. Furthermore, in one or more implementations, the disclosed systems generate a synthesized texture utilizing the kerning-value-adjusted glyphs by utilizing image inpainting on the textures corresponding to the kerning-value-adjusted glyphs. Moreover, in certain instances, the disclosed systems apply a target texture to a target digital text based on the generated synthesized texture.
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公开(公告)号：US20220414314A1
公开(公告)日：2022-12-29
申请号：US17362031
申请日：2021-06-29
Applicant: Adobe Inc.
Inventor： Zhifei Zhang , Zhaowen Wang , Hailin Jin , Matthew Fisher
IPC: G06F40/109 , G06T11/20 , G06N3/04
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly generating scalable and semantically editable font representations utilizing a machine learning approach. For example, the disclosed systems generate a font representation code from a glyph utilizing a particular neural network architecture. For example, the disclosed systems utilize a glyph appearance propagation model and perform an iterative process to generate a font representation code from an initial glyph. Additionally, using a glyph appearance propagation model, the disclosed systems automatically propagate the appearance of the initial glyph from the font representation code to generate additional glyphs corresponding to respective glyph labels. In some embodiments, the disclosed systems propagate edits or other changes in appearance of a glyph to other glyphs within a glyph set (e.g., to match the appearance of the edited glyph).
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公开(公告)号：US20220319065A1
公开(公告)日：2022-10-06
申请号：US17219391
申请日：2021-03-31
Applicant: Adobe Inc.
Inventor： Nirmal Kumawat , Zhaowen Wang , Zhifei Zhang
Abstract: This disclosure describes one or more implementations of systems, non-transitory computer-readable media, and methods that extract a texture from embedded text within a digital image utilizing kerning-adjusted glyphs. For example, the disclosed systems utilize text recognition and text segmentation to identify and segment glyphs from embedded text depicted in a digital image. Subsequently, in some implementations, the disclosed systems determine optimistic kerning values between consecutive glyphs and utilize the kerning values to reduce gaps between the consecutive glyphs. Furthermore, in one or more implementations, the disclosed systems generate a synthesized texture utilizing the kerning-value-adjusted glyphs by utilizing image inpainting on the textures corresponding to the kerning-value-adjusted glyphs. Moreover, in certain instances, the disclosed systems apply a target texture to a target digital text based on the generated synthesized texture.
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公开(公告)号：US11288771B2
公开(公告)日：2022-03-29
申请号：US16861688
申请日：2020-04-29
Applicant: ADOBE INC.
Inventor： Yulun Zhang , Zhifei Zhang , Jose Ignacio Echevarria Vallespi , Zhaowen Wang , Stephen Diverdi
IPC: G06T3/40
Abstract: Systems and methods for texture hallucination with a large upscaling factor are described. Embodiments of the systems and methods may receive an input image and a reference image, extract an upscaled feature map from the input image, match the input image to a portion of the reference image, wherein a resolution of the reference image is higher than a resolution of the input image, concatenate the upscaled feature map with a reference feature map corresponding to the portion of the reference image to produce a concatenated feature map, and generate a reconstructed image based on the concatenated feature map using a machine learning model trained with a texture loss and a degradation loss, wherein the texture loss is based on a high frequency band filter, and the degradation loss is based on a downscaled version of the reconstructed image.
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公开(公告)号：US20210342974A1
公开(公告)日：2021-11-04
申请号：US16861688
申请日：2020-04-29
Applicant: ADOBE INC.
Inventor： Yulun Zhang , Zhifei Zhang , Jose Ignacio Echevarria Vallespi , Zhaowen Wang , Stephen Diverdi
Abstract: Systems and methods for texture hallucination with a large upscaling factor are described. Embodiments of the systems and methods may receive an input image and a reference image, extract an upscaled feature map from the input image, match the input image to a portion of the reference image, wherein a resolution of the reference image is higher than a resolution of the input image, concatenate the upscaled feature map with a reference feature map corresponding to the portion of the reference image to produce a concatenated feature map, and generate a reconstructed image based on the concatenated feature map using a machine learning model trained with a texture loss and a degradation loss, wherein the texture loss is based on a high frequency band filter, and the degradation loss is based on a downscaled version of the reconstructed image.
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Patent Agency Ranking
公开(公告)号：US10650495B2
公开(公告)日：2020-05-12
申请号：US15997386
申请日：2018-06-04
Applicant: Adobe Inc.
Inventor： Zhifei Zhang , Zhe Lin , Zhaowen Wang
Abstract: High resolution style transfer techniques and systems are described that overcome the challenges of transferring high resolution style features from one image to another image, and of the limited availability of training data to perform high resolution style transfer. In an example, a neural network is trained using high resolution style features which are extracted from a style image and are used in conjunction with an input image to apply the style features to the input image to generate a version of the input image transformed using the high resolution style features.
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公开(公告)号：US12271983B2
公开(公告)日：2025-04-08
申请号：US17809494
申请日：2022-06-28
Applicant: Adobe Inc.
Inventor： Zhifei Zhang , Zhe Lin , Scott Cohen , Kevin Gary Smith
IPC: G06T11/60 , G06F3/0482 , G06F16/532 , G06T11/20
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that implements related image search and image modification processes using various search engines and a consolidated graphical user interface. For instance, in one or more embodiments, the disclosed systems receive an input digital image and search input and further modify the input digital image using the image search results retrieved in response to the search input. In some cases, the search input includes a multi-modal search input having multiple queries (e.g., an image query and a text query), and the disclosed systems retrieve the image search results utilizing a weighted combination of the queries. In some implementations, the disclosed systems generate an input embedding for the search input (e.g., the multi-modal search input) and retrieve the image search results using the input embedding.
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公开(公告)号：US12235891B2
公开(公告)日：2025-02-25
申请号：US17809503
申请日：2022-06-28
Applicant: Adobe Inc.
Inventor： Zhifei Zhang , Zhe Lin
IPC: G06F16/33 , G06F16/3332 , G06F16/532 , G06F16/535
Abstract: Systems, methods, and non-transitory computer-readable media implements related image search and image modification processes using various search engines and a consolidated graphical user interface. For instance, one or more embodiments involve receiving an input digital image and search input and further modifying the input digital image using the image search results retrieved in response to the search input. In some cases, the search input includes a multi-modal search input having multiple queries (e.g., an image query and a text query), and one or more embodiments involve retrieving the image search results utilizing a weighted combination of the queries. Some implementations involve generating an input embedding for the search input (e.g., the multi-modal search input) and retrieving the image search results using the input embedding.
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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：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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