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    DEEP FEATURE GENERATIVE ADVERSARIAL NEURAL NETWORKS
    21.
    发明申请
    DEEP FEATURE GENERATIVE ADVERSARIAL NEURAL NETWORKS 有权

    公开(公告)号：US20210383509A1

    公开(公告)日：2021-12-09

    申请号：US17445362

    申请日：2021-08-18

    Applicant: Snap Inc.

    Inventor： Sergey Demyanov ,  Aleksei Podkin ,  Aleksei Stoliar ,  Vadim Velicodnii ,  Fedor Zhdanov

    IPC: G06T5/00 ,  G06T5/10

    Abstract: A mobile device can implement a neural network-based domain transfer scheme to modify an image in a first domain appearance to a second domain appearance. The domain transfer scheme can be configured to detect an object in the image, apply an effect to the image, and blend the image using color space adjustments and blending schemes to generate a realistic result image. The domain transfer scheme can further be configured to efficiently execute on the constrained device by removing operational layers based on resources available on the mobile device.

    Deep feature generative adversarial neural networks
    22.
    发明授权
    Deep feature generative adversarial neural networks 有权

    公开(公告)号：US11120526B1

    公开(公告)日：2021-09-14

    申请号：US16376564

    申请日：2019-04-05

    Applicant: Snap Inc.

    Inventor： Sergey Demyanov ,  Aleksei Podkin ,  Aleksei Stoliar ,  Vadim Velicodnii ,  Fedor Zhdanov

    IPC: G06T5/00 ,  G06T5/10 ,  H04L12/58

    Abstract: A mobile device can implement a neural network-based domain transfer scheme to modify an image in a first domain appearance to a second domain appearance. The domain transfer scheme can be configured to detect an object in the image, apply an effect to the image, and blend the image using color space adjustments and blending schemes to generate a realistic result image. The domain transfer scheme can further be configured to efficiently execute on the constrained device by removing operational layers based on resources available on the mobile device.

    NEURAL SHADING OF REFLECTIVE SURFACES
    25.
    发明公开
    NEURAL SHADING OF REFLECTIVE SURFACES 审中-公开

    公开(公告)号：US20240303902A1

    公开(公告)日：2024-09-12

    申请号：US18182117

    申请日：2023-03-10

    Applicant: SNAP INC.

    Inventor： Vladislav Shakhrai ,  Sergey Demyanov ,  Aleksei Stoliar ,  Istvan Marton

    IPC: G06T15/04 ,  G06T15/00

    CPC classification number: G06T15/04 ,  G06T15/005

    Abstract: The subject technology receives an object mesh, information related to a viewpoint for rendering an image of an object having a reflective surface, and a set of maps. The subject technology generates a rasterized RGB (Red Green Blue) image based on the object mesh, the viewpoint, and the set of maps. The subject technology generates, using a neural network model, an output image of the object with the reflective surface based at least in part on the rasterized RGB image and the viewpoint. The subject technology provides for display the output image of the object with the reflective surface on a display of a computer client device.

    AUTOMATED AUGMENTED REALITY EXPERIENCE CREATION SYSTEM
    27.
    发明公开
    AUTOMATED AUGMENTED REALITY EXPERIENCE CREATION SYSTEM 审中-公开

    公开(公告)号：US20230386144A1

    公开(公告)日：2023-11-30

    申请号：US17804500

    申请日：2022-05-27

    Applicant: Snap Inc.

    Inventor： Konstantin Gudkov ,  Andrei Zharkov ,  Vadim Velicodnii ,  Aleksei Zhuravlev ,  Sergey Demyanov

    IPC: G06T19/00 ,  G06F3/01 ,  G06F3/04815 ,  G06F8/34

    CPC classification number: G06T19/006 ,  G06F3/011 ,  G06F3/04815 ,  G06F8/34

    Abstract: Methods and systems are disclosed for performing automatically creating AR experiences on a messaging platform. The methods and systems perform operations that include: receiving, via a graphical user interface (GUI), input that specifies a plurality of image transformation parameters; accessing a set of sample source images; modifying the set of sample source images based on the plurality of image transformation parameters to generate a set of sample target images; training a machine learning model to generate a given target image from a given source image by establishing a relationship between the set of sample source images and the set of sample target images; and automatically generating an augmented reality experience comprising the trained machine learning model.

    PROTECTING IMAGE FEATURES IN STYLIZED REPRESENTATIONS OF A SOURCE IMAGE
    29.
    发明公开
    PROTECTING IMAGE FEATURES IN STYLIZED REPRESENTATIONS OF A SOURCE IMAGE 审中-公开

    公开(公告)号：US20230215062A1

    公开(公告)日：2023-07-06

    申请号：US17804268

    申请日：2022-05-26

    Applicant: Snap Inc.

    Inventor： Konstantin Gudkov ,  Sergey Demyanov ,  Andrei Zharkov ,  Fedor Zhdanov ,  Vadim Velicodnii

    IPC: G06T11/60 ,  G06N20/20

    CPC classification number: G06T11/60 ,  G06N20/20 ,  G06T2210/44

    Abstract: Systems and methods herein describe an image stylization system. The image stylization system accesses a set of images corresponding to a target domain style, generates a set of paired images using a first machine learning model, analyze the generated set of paired images using a second machine learning model trained to analyze the generated set of paired images based on a plurality of protected feature criteria, determines a set of image transformations for the generated set of pairs, generates a transformed set of paired images by performing the set of image transformations on the set of paired images, and generates stylized images corresponding to the target domain style using a supervised image translation model trained on the transformed set of paired images.

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