Color transforms using static shaders compiled at initialization

    公开(公告)号:US11423588B2

    公开(公告)日:2022-08-23

    申请号:US16674446

    申请日:2019-11-05

    Applicant: Adobe Inc.

    Abstract: A method, in which one or more processing devices perform operations, includes compiling a static shader at initialization of a media-processing application. The static shader is configured to transform color data from multiple pre-transform color spaces to multiple post-transform color spaces. A runtime of the media-processing application occurs subsequent to the initialization, and the method further includes determining, during the runtime, that the static shader is applicable to a color transform from a pre-transform color space to a post-transform color space. The method further includes executing the static shader to perform the color transform, based on determining that the static shader is applicable to the color transform.

    Image Content Snapping Guidelines

    公开(公告)号:US20220122258A1

    公开(公告)日:2022-04-21

    申请号:US17071157

    申请日:2020-10-15

    Applicant: Adobe Inc.

    Abstract: In implementations of image content snapping guidelines, a guidelines segmentation system includes modules, such as an image pre-processing module to reduce the image size of a digital image if the image size exceeds an image size threshold. An object segmentation module segments objects depicted in the digital image and identifies each object by a bounding border that delineates an object region boundary. An edge detection module receives a segmented object and determines object external edges and object feature edges from the segmented object, and identifies object corners of the object. A snapping guidelines module determines image content snapping guidelines of an object depicted in the digital image, the image content snapping guidelines for an object determined based on the bounding border of the object region boundary, the object external edges, the object feature edges, and projected snapping guidelines that extend from the object corners of the object.

    Searching for images using generated images

    公开(公告)号:US12197496B1

    公开(公告)日:2025-01-14

    申请号:US18361822

    申请日:2023-07-29

    Applicant: Adobe Inc.

    Abstract: In implementations of systems for searching for images using generated images, a computing device implements a search system to receive a natural language search query for digital images included in a digital image repository. The search system generates a set of digital images using a machine learning model based on the natural language search query. The machine learning model is trained on training data to generate digital images based on natural language inputs. The search system performs an image-based search for digital images included in the digital image repository using the set of digital images. An indication of the search result is generated for display in a user interface based on performing the image-based search.

    Image content snapping guidelines

    公开(公告)号:US11562488B2

    公开(公告)日:2023-01-24

    申请号:US17071157

    申请日:2020-10-15

    Applicant: Adobe Inc.

    Abstract: In implementations of image content snapping guidelines, a guidelines segmentation system includes modules, such as an image pre-processing module to reduce the image size of a digital image if the image size exceeds an image size threshold. An object segmentation module segments objects depicted in the digital image and identifies each object by a bounding border that delineates an object region boundary. An edge detection module receives a segmented object and determines object external edges and object feature edges from the segmented object, and identifies object corners of the object. A snapping guidelines module determines image content snapping guidelines of an object depicted in the digital image, the image content snapping guidelines for an object determined based on the bounding border of the object region boundary, the object external edges, the object feature edges, and projected snapping guidelines that extend from the object corners of the object.

    TRANSFERRING HAIRSTYLES BETWEEN PORTRAIT IMAGES UTILIZING DEEP LATENT REPRESENTATIONS

    公开(公告)号:US20240005578A1

    公开(公告)日:2024-01-04

    申请号:US18467397

    申请日:2023-09-14

    Applicant: Adobe Inc.

    CPC classification number: G06T11/60 G06N3/08 G06T5/50 G06V40/165 G06V40/171

    Abstract: The disclosure describes one or more embodiments of systems, methods, and non-transitory computer-readable media that generate a transferred hairstyle image that depicts a person from a source image having a hairstyle from a target image. For example, the disclosed systems utilize a face-generative neural network to project the source and target images into latent vectors. In addition, in some embodiments, the disclosed systems quantify (or identify) activation values that control hair features for the projected latent vectors of the target and source image. Furthermore, in some instances, the disclosed systems selectively combine (e.g., via splicing) the projected latent vectors of the target and source image to generate a hairstyle-transfer latent vector by using the quantified activation values. Then, in one or more embodiments, the disclosed systems generate a transferred hairstyle image that depicts the person from the source image having the hairstyle from the target image by synthesizing the hairstyle-transfer latent vector.

    TRANSFERRING HAIRSTYLES BETWEEN PORTRAIT IMAGES UTILIZING DEEP LATENT REPRESENTATIONS

    公开(公告)号:US20220101577A1

    公开(公告)日:2022-03-31

    申请号:US17034845

    申请日:2020-09-28

    Applicant: Adobe Inc.

    Abstract: The disclosure describes one or more embodiments of systems, methods, and non-transitory computer-readable media that generate a transferred hairstyle image that depicts a person from a source image having a hairstyle from a target image. For example, the disclosed systems utilize a face-generative neural network to project the source and target images into latent vectors. In addition, in some embodiments, the disclosed systems quantify (or identify) activation values that control hair features for the projected latent vectors of the target and source image. Furthermore, in some instances, the disclosed systems selectively combine (e.g., via splicing) the projected latent vectors of the target and source image to generate a hairstyle-transfer latent vector by using the quantified activation values. Then, in one or more embodiments, the disclosed systems generate a transferred hairstyle image that depicts the person from the source image having the hairstyle from the target image by synthesizing the hairstyle-transfer latent vector.

    Evenly Spaced Curve Sampling Technique for Digital Visual Content Transformation

    公开(公告)号:US20210125316A1

    公开(公告)日:2021-04-29

    申请号:US16666179

    申请日:2019-10-28

    Applicant: Adobe Inc.

    Abstract: A curve sampling technique for generating transformed digital visual content is leveraged in a digital medium environment. Initially, a curve sampling system obtains digital visual content, e.g., images and videos. The curve sampling system generates transformed digital visual content by transforming one or more pixels of the digital visual content using a lookup table that is derived from samples of a curve taken at evenly spaced intervals along a y-axis of a graph of the curve. Broadly speaking, the curve defines how to transform a visual characteristic of the pixels in order to achieve a desired digital visual content transformation. Additionally, the curve sampling may correspond to one step in a series of steps for transforming colors of digital visual content. Indeed, such transformations may involve multiple curve sampling steps.

    Vector Graphic Font Character Generation Techniques

    公开(公告)号:US20200258273A1

    公开(公告)日:2020-08-13

    申请号:US16271598

    申请日:2019-02-08

    Applicant: Adobe Inc.

    Abstract: Vector graphic font generation system implemented as part of a computing device is described. The system is configured to improve generate vector graphic font characters by detecting an object within a digital image, segmenting the digital image extract the facial region within the digital image, generating a vector graphic by converting a format of the segmented digital image into a scalable vector format, mapping the vector graphic with Unicode characters, and subsequently mapping the Unicode character with a glyph identifier. The vector graphic font generation system described herein enables the expression of a wide spectrum of emotions in numerous applications using font characters that precisely match the object, e.g., facial appearance of users as depicted in digital images.

    SEARCHING FOR IMAGES USING GENERATED IMAGES

    公开(公告)号:US20250036678A1

    公开(公告)日:2025-01-30

    申请号:US18361822

    申请日:2023-07-29

    Applicant: Adobe Inc.

    Abstract: In implementations of systems for searching for images using generated images, a computing device implements a search system to receive a natural language search query for digital images included in a digital image repository. The search system generates a set of digital images using a machine learning model based on the natural language search query. The machine learning model is trained on training data to generate digital images based on natural language inputs. The search system performs an image-based search for digital images included in the digital image repository using the set of digital images. An indication of the search result is generated for display in a user interface based on performing the image-based search.

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