DESIGN COMPOSITING USING IMAGE HARMONIZATION

    公开(公告)号:US20240420394A1

    公开(公告)日:2024-12-19

    申请号:US18334610

    申请日:2023-06-14

    Applicant: ADOBE INC.

    Abstract: Systems and methods are provided for image editing, and more particularly, for harmonizing background images with text. Embodiments of the present disclosure obtain an image including text and a region overlapping the text. In some aspects, the text includes a first color. Embodiments then select a second color that contrasts with the first color, and generate a modified image including the text and a modified region using a machine learning model that takes the image and the second color as input. The modified image is generated conditionally, so as to include the second color in a region corresponding to the text.

    GENERATING PERSONALIZED DIGITAL DESIGN TEMPLATE RECOMMENDATIONS

    公开(公告)号:US20240119230A1

    公开(公告)日:2024-04-11

    申请号:US17938253

    申请日:2022-10-05

    Applicant: Adobe Inc.

    CPC classification number: G06F40/186 G06F40/30 G06N3/08

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that provides to a user a subset of digital design templates as recommendations based on a creative segment classification and template classifications. For instance, in one or more embodiments, the disclosed systems generate the creative segment classification for the user and determines geo-seasonal intent data. Furthermore, the disclosed system generates template classifications using a machine learning model based on geo-seasonality and creative intent. In doing so, the disclosed system identifies a subset of digital design templates based on the template classifications, geo-seasonal intent data, and the creative segment classification of the user.

    TECHNIQUES FOR SMOOTH REGION MERGING IN IMAGE EDITING

    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.

    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.

    Utilizing a transformer-based generative language model to generate digital design document variations

    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.

    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.

    Generating personalized digital design template recommendations

    公开(公告)号:US11989505B2

    公开(公告)日:2024-05-21

    申请号:US17938253

    申请日:2022-10-05

    Applicant: Adobe Inc.

    CPC classification number: G06F40/186 G06F40/30 G06N3/08

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that provides to a user a subset of digital design templates as recommendations based on a creative segment classification and template classifications. For instance, in one or more embodiments, the disclosed systems generate the creative segment classification for the user and determines geo-seasonal intent data. Furthermore, the disclosed system generates template classifications using a machine learning model based on geo-seasonality and creative intent. In doing so, the disclosed system identifies a subset of digital design templates based on the template classifications, geo-seasonal intent data, and the creative segment classification of the user.

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