Interacting with visual codes within messaging system

    公开(公告)号:US11983390B2

    公开(公告)日:2024-05-14

    申请号:US17820674

    申请日:2022-08-18

    Applicant: Snap Inc.

    Inventor: Vadim Velicodnii

    CPC classification number: G06F3/0484 G06F3/0482 H04L51/07

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for interacting with visual codes within a messaging system. The program and method provide for displaying, by a messaging application, captured image data comprising a visual code, the visual code including a custom graphic and being decodable to access a first feature of the messaging application; receiving user input selecting the visual code; displaying an updated version of the custom graphic; providing an animation which depicts the updated version of the custom graphic as moving from the visual code to an interface element comprising a group of icons, each icon within the group of icons being user-selectable to access a respective second feature of the messaging application; and updating the group of icons to include an additional icon which is user-selectable to access the first feature of the messaging application.

    DEEP FEATURE GENERATIVE ADVERSARIAL NEURAL NETWORKS

    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.

    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

    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.

    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.

    INTERACTING WITH VISUAL CODES WITHIN MESSAGING SYSTEM

    公开(公告)号:US20240281121A1

    公开(公告)日:2024-08-22

    申请号:US18634020

    申请日:2024-04-12

    Applicant: Snap Inc.

    Inventor: Vadim Velicodnii

    CPC classification number: G06F3/0484 G06F3/0482 H04L51/07

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for interacting with visual codes within a messaging system. The program and method provide for displaying, by a messaging application, captured image data comprising a visual code, the visual code including a custom graphic and being decodable to access a first feature of the messaging application; receiving user input selecting the visual code; displaying an updated version of the custom graphic; providing an animation which depicts the updated version of the custom graphic as moving from the visual code to an interface element comprising a group of icons, each icon within the group of icons being user-selectable to access a respective second feature of the messaging application; and updating the group of icons to include an additional icon which is user-selectable to access the first feature of the messaging application.

    INTERACTING WITH VISUAL CODES WITHIN MESSAGING SYSTEM

    公开(公告)号:US20240061554A1

    公开(公告)日:2024-02-22

    申请号:US17820674

    申请日:2022-08-18

    Applicant: Snap Inc.

    Inventor: Vadim Velicodnii

    CPC classification number: G06F3/0484 G06F3/0482 H04L51/07

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for interacting with visual codes within a messaging system. The program and method provide for displaying, by a messaging application, captured image data comprising a visual code, the visual code including a custom graphic and being decodable to access a first feature of the messaging application; receiving user input selecting the visual code; displaying an updated version of the custom graphic; providing an animation which depicts the updated version of the custom graphic as moving from the visual code to an interface element comprising a group of icons, each icon within the group of icons being user-selectable to access a respective second feature of the messaging application; and updating the group of icons to include an additional icon which is user-selectable to access the first feature of the messaging application.

    AUTOMATED AUGMENTED REALITY EXPERIENCE CREATION SYSTEM

    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.

    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.

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