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公开(公告)号：US20240127577A1
公开(公告)日：2024-04-18
申请号：US17965291
申请日：2022-10-13
Applicant: Adobe Inc.
CPC classification number: G06V10/761 , G06T11/60
Abstract: In implementations of systems for generating templates using structure-based matching, a computing device implements a template system to receive input data describing a set of digital design elements. The template system represents the input data as a sentence in a design structure language that describes structural relationships between design elements included in the set of digital design elements. An input template embedding is generated based on the sentence in the design structure language. The template system generates a digital template that includes the set of digital design elements for display in a user interface based on the input template embedding.
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公开(公告)号：US20250148670A1
公开(公告)日：2025-05-08
申请号：US18502778
申请日：2023-11-06
Applicant: Adobe Inc.
Inventor： Marian Lupascu , Vlad-Constantin Lungu-Stan , Ionut Mironica , George Bogdan Avram
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating digital designs utilizing a diffusion neural network to preserve readability and design composition while modifying image content background images and design assets. In some embodiments, the disclosed systems access a text prompt defining visual attributes of a digital design. Furthermore, the disclosed systems generate a modified text prompt by replacing chromatic information within the text prompt. Additionally, the disclosed systems determine an adaptive strength for a diffusion neural network from the text prompt. Also, the disclosed systems generate a modified digital design utilizing the diffusion neural network to process the modified text prompt according to the adaptive strength.
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公开(公告)号：US20250095256A1
公开(公告)日：2025-03-20
申请号：US18890203
申请日：2024-09-19
Applicant: ADOBE INC.
Inventor： Vlad-Constantin Lungu-Stan , Marian Lupascu , Ionut Mironicä
Abstract: A method, apparatus, non-transitory computer readable medium, and system for generating images with a particular style that fit coherently into a scene includes obtaining a text prompt and a preliminary style image. The text prompt describes an image element, and the preliminary style image includes a region with a target style. Embodiments then extract the region with the target style from the preliminary style image to obtain a style image. Embodiments subsequently generate, using an image generation model, a synthetic image based on the text prompt and the style image. The synthetic image depicts the image element with the target style.
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公开(公告)号：US20250095226A1
公开(公告)日：2025-03-20
申请号：US18884787
申请日：2024-09-13
Applicant: ADOBE INC.
Inventor： Adrian-Stefan Ungureanu-Contes , Marian Lupascu , Vlad-Constantin Lungu-Stan , Ionut Mironicä , Vineet Batra
IPC: G06T11/00 , G06F3/04847
Abstract: A method, apparatus, non-transitory computer readable medium, and system for generating images with an adjustable level of complexity includes obtaining a content prompt, a style prompt, and a complexity value. The content prompt describes an image element, the style prompt indicates an image style, and the complexity value indicates a level of influence of the style prompt. Embodiments then generate, using an image generation model, an output image based on the content prompt, the style prompt, and the complexity value, wherein the output image includes the image element with a level of the image style based on the complexity value.
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公开(公告)号：US12254170B2
公开(公告)日：2025-03-18
申请号：US18313529
申请日：2023-05-08
Applicant: Adobe Inc.
IPC: G06Q30/02 , G06F3/04845 , G06F40/106 , G06F40/284 , G06T7/60
Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a design language model and a generative language model to generate digital design documents with design variations. In particular embodiments, the disclosed systems implement the design language model to tokenize the design of a document into a sequence of language tokens. For example, the disclosed systems tokenize visual elements and a layout of the document—in addition to optional user-added content. The generative language model utilizes the sequence of language tokens to predict a next language token representing a suggested design variation. Based on the predicted language token, the disclosed systems generate a modified digital design document visually portraying the suggested design variation. Further, in one or more embodiments, the disclosed systems perform iterative refinements to the modified digital design document.
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Patent Agency Ranking
6.发明公开公开(公告)号：US20230305690A1
公开(公告)日：2023-09-28
申请号：US18313529
申请日：2023-05-08
Applicant: Adobe Inc.
IPC: G06F3/04845 , G06F40/106 , G06F40/284 , G06T7/60
CPC classification number: G06F3/04845 , G06F40/106 , G06F40/284 , G06T7/60
Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a design language model and a generative language model to generate digital design documents with design variations. In particular embodiments, the disclosed systems implement the design language model to tokenize the design of a document into a sequence of language tokens. For example, the disclosed systems tokenize visual elements and a layout of the document—in addition to optional user-added content. The generative language model utilizes the sequence of language tokens to predict a next language token representing a suggested design variation. Based on the predicted language token, the disclosed systems generate a modified digital design document visually portraying the suggested design variation. Further, in one or more embodiments, the disclosed systems perform iterative refinements to the modified digital design document.
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公开(公告)号：US20250131604A1
公开(公告)日：2025-04-24
申请号：US18491472
申请日：2023-10-20
Applicant: ADOBE INC.
Inventor： Adrian-Stefan Ungureanu , Vlad-Constantin Lungu-Stan , Ionut Mironicã
IPC: G06T11/00 , G06F3/04845 , G06F3/04847
Abstract: Embodiments include obtaining a prompt and a diversity input indicating a level of adherence to the prompt. The diversity input may be implemented as a graphical user interface (GUI) element, such as a slider or field. Embodiments then generate a guidance embedding based on the prompt and the diversity input. Embodiments update the guidance embedding based on the diversity input. Subsequently, embodiments generate a synthetic image based on the guidance embedding, wherein the synthetic image depicts an element of the prompt based on the level of adherence from the diversity input.
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公开(公告)号：US20250111137A1
公开(公告)日：2025-04-03
申请号：US18477978
申请日：2023-09-29
Applicant: ADOBE INC.
IPC: G06F40/186 , G06F40/126 , G06F40/30 , G06F40/40
Abstract: Systems and methods for generating full designs from text include retrieving a plurality of document templates based on a design prompt, and filtering the document templates based on an image prompt. A document template is then selected based on the filtering, and a document is generated based on the document template and the image prompt. Embodiments are further configured to generate content from one or more of the prompts, where the content is included in the final design document.
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公开(公告)号：US20250095227A1
公开(公告)日：2025-03-20
申请号：US18886452
申请日：2024-09-16
Applicant: ADOBE INC.
Inventor： Adrian-Stefan Ungureanu-Contes , Marian Lupascu , Vlad-Constantin Lungu-Stan , Ionuţ Mironica , Vineet Batra
IPC: G06T11/00 , G06T3/4053
Abstract: A method, apparatus, non-transitory computer readable medium, and system for training a text-guided vector image synthesis include obtaining training data including a vectorizable image and a caption describing the vectorizable image and generating, using an image generation model, a predicted image with a first level of high frequency detail. Then, the training data and the predicted image are used to tune the image generation model to generate a synthetic vectorizable image based on the caption, where the synthetic vectorizable image has a second level of high frequency detail that is lower than the first level of high frequency detail of the predicted image.
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10.发明授权公开(公告)号：US11644961B1
公开(公告)日：2023-05-09
申请号：US17652044
申请日：2022-02-22
Applicant: Adobe Inc.
IPC: G06Q30/02 , G06F3/04845 , G06F40/106 , G06F40/284 , G06T7/60
CPC classification number: G06F3/04845 , G06F40/106 , G06F40/284 , G06T7/60
Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a design language model and a generative language model to generate digital design documents with design variations. In particular embodiments, the disclosed systems implement the design language model to tokenize the design of a document into a sequence of language tokens. For example, the disclosed systems tokenize visual elements and a layout of the document—in addition to optional user-added content. The generative language model utilizes the sequence of language tokens to predict a next language token representing a suggested design variation. Based on the predicted language token, the disclosed systems generate a modified digital design document visually portraying the suggested design variation. Further, in one or more embodiments, the disclosed systems perform iterative refinements to the modified digital design document.
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