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    SUPERVISED LEARNING TECHNIQUES FOR ENCODER TRAINING
    11.
    发明申请
    SUPERVISED LEARNING TECHNIQUES FOR ENCODER TRAINING 有权

    公开(公告)号：US20220121932A1

    公开(公告)日：2022-04-21

    申请号：US17384378

    申请日：2021-07-23

    Applicant: Adobe Inc.

    Inventor： Ratheesh Kalarot ,  Wei-An Lin ,  Cameron Smith ,  Zhixin Shu ,  Baldo Faieta ,  Shabnam Ghadar ,  Jingwan Lu ,  Aliakbar Darabi ,  Jun-Yan Zhu ,  Niloy Mitra ,  Richard Zhang ,  Elya Shechtman

    IPC: G06N3/08 ,  G06N3/04

    Abstract: Systems and methods train an encoder neural network for fast and accurate projection into the latent space of a Generative Adversarial Network (GAN). The encoder is trained by providing an input training image to the encoder and producing, by the encoder, a latent space representation of the input training image. The latent space representation is provided as input to the GAN to generate a generated training image. A latent code is sampled from a latent space associated with the GAN and the sampled latent code is provided as input to the GAN. The GAN generates a synthetic training image based on the sampled latent code. The sampled latent code is provided as input to the encoder to produce a synthetic training code. The encoder is updated by minimizing a loss between the generated training image and the input training image, and the synthetic training code and the sampled latent code.

    INTELLIGENTLY SENSING DIGITAL USER CONTEXT TO GENERATE RECOMMENDATIONS ACROSS CLIENT DEVICE APPLICATIONS
    13.
    发明申请
    INTELLIGENTLY SENSING DIGITAL USER CONTEXT TO GENERATE RECOMMENDATIONS ACROSS CLIENT DEVICE APPLICATIONS 有权

    公开(公告)号：US20220113996A1

    公开(公告)日：2022-04-14

    申请号：US17069637

    申请日：2020-10-13

    Applicant: Adobe Inc.

    Inventor： Oliver Brdiczka ,  Robert Alley ,  Kyoung Tak Kim ,  Kevin Gary Smith ,  Aliakbar Darabi

    IPC: G06F9/451 ,  G06N20/00 ,  G06F11/34 ,  G06T11/00

    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.

    Patch validity test
    14.
    发明授权
    Patch validity test 有权

    公开(公告)号：US10586311B2

    公开(公告)日：2020-03-10

    申请号：US15921457

    申请日：2018-03-14

    Applicant: ADOBE INC.

    Inventor： Sohrab Amirghodsi ,  Kevin Wampler ,  Elya Shechtman ,  Aliakbar Darabi

    IPC: G06T5/00 ,  G06T5/20 ,  G06K9/62 ,  G06T11/60

    Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for improved patch validity testing for patch-based synthesis applications using similarity transforms. The improved patch validity tests are used to validate (or invalidate) candidate patches as valid patches falling within a sampling region of a source image. The improved patch validity tests include a hole dilation test for patch validity, a no-dilation test for patch invalidity, and a comprehensive pixel test for patch invalidity. A fringe test for range invalidity can be used to identify pixels with an invalid range and invalidate corresponding candidate patches. The fringe test for range invalidity can be performed as a precursor to any or all of the improved patch validity tests. In this manner, validated candidate patches are used to automatically reconstruct a target image.

    Controlling smoothness of a transition between images
    15.
    发明授权
    Controlling smoothness of a transition between images 有权

    公开(公告)号：US10402948B2

    公开(公告)日：2019-09-03

    申请号：US16009714

    申请日：2018-06-15

    Applicant: ADOBE INC.

    Inventor： Sylvain Paris ,  Sohrab Amirghodsi ,  Aliakbar Darabi ,  Elya Shechtman

    IPC: G06T5/50 ,  G06T5/00 ,  G06T3/40 ,  G06T11/60

    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.

    Intelligently generating client device application recommendations based on dynamic digital user context states
    16.
    发明授权
    Intelligently generating client device application recommendations based on dynamic digital user context states 有权

    公开(公告)号：US12159151B2

    公开(公告)日：2024-12-03

    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

    IPC: G06F9/451 ,  G06F11/34 ,  G06N20/00 ,  G06T11/00

    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.

    Classifying image styles of images based on image style embeddings
    19.
    发明授权
    Classifying image styles of images based on image style embeddings 有权

    公开(公告)号：US11620330B2

    公开(公告)日：2023-04-04

    申请号：US16897008

    申请日：2020-06-09

    Applicant: ADOBE INC.

    Inventor： Devavrat Tomar ,  Aliakbar Darabi

    IPC: G06F16/55 ,  G06F16/583 ,  G06N3/08 ,  G06N20/00 ,  G06K9/62 ,  G06V10/44

    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.

    DETAIL-PRESERVING IMAGE EDITING TECHNIQUES
    20.
    发明申请
    DETAIL-PRESERVING IMAGE EDITING TECHNIQUES 有权

    公开(公告)号：US20220122307A1

    公开(公告)日：2022-04-21

    申请号：US17468511

    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

    IPC: G06T11/60 ,  G06T3/00 ,  G06T3/40

    Abstract: Systems and methods combine an input image with an edited image generated using a generator neural network to preserve detail from the original image. A computing system provides an input image to a machine learning model to generate a latent space representation of the input image. The system provides the latent space representation to a generator neural network to generate a generated image. The system generates multiple scale representations of the input image, as well as multiple scale representations of the generated image. The system generates a first combined image based on first scale representations of the images and a first value. The system generates a second combined image based on second scale representations of the images and a second value. The system blends the first combined image with the second combined image to generate an output image.

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