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    GENERATING DATA IN A MESSAGING SYSTEM FOR A MACHINE LEARNING MODEL
    3.
    发明公开
    GENERATING DATA IN A MESSAGING SYSTEM FOR A MACHINE LEARNING MODEL 审中-公开

    公开(公告)号：US20230153396A1

    公开(公告)日：2023-05-18

    申请号：US18151268

    申请日：2023-01-06

    Applicant: Snap Inc.

    Inventor： Zehao Xue ,  Zhou Ren

    IPC: G06F18/40 ,  G06N20/00 ,  G06F18/214

    CPC classification number: G06F18/40 ,  G06N20/00 ,  G06F18/214 ,  G06V2201/10 ,  G06V20/68

    Abstract: Systems and methods are provided for analyzing, by a computing device, location data associated with a location of the computing device to determine that an image or video captured using a messaging application on the computing device is captured near a food-related venue or event, receiving input related to food associated with the food-related venue or event, sending the image or video and the input related to food associated with the food-related venue or event to a computing system to train a machine learning model for food detection, and updating the messaging application to comprise the trained machine learning model for food detection.

    Query matching to media collections in a messaging system
    5.
    发明授权
    Query matching to media collections in a messaging system 有权

    公开(公告)号：US10664512B1

    公开(公告)日：2020-05-26

    申请号：US15895821

    申请日：2018-02-13

    Applicant: Snap Inc.

    Inventor： Xinran He ,  Jie Luo ,  Sushobhan Nayak ,  Zhou Ren ,  Christophe Jacky Henri Van Gysel

    IPC: G06F16/435 ,  G06Q50/00 ,  G06N20/00 ,  G06F16/951 ,  G06F16/2457

    Abstract: Systems and methods are provided for generating training data from queries and user interactions associated with media collections related to the queries, and training a machine learning model using the generated training data to generate a trained machine learning model. The systems and methods further provide for receiving a prediction request comprising a query for relevant media collections, analyzing the query to determine query features, determining a plurality of media collections for the query, analyzing the plurality of media collections to determine media collection features for each media collection of the plurality of media collections, and generating, using the trained machine learning model, a semantic matching score for each media collection of the plurality of media collections based on matching the query features to the media collection features for each media collection of the plurality of media collections.

    Generating data in a messaging system for a machine learning model
    7.
    发明授权
    Generating data in a messaging system for a machine learning model 有权

    公开(公告)号：US11599741B1

    公开(公告)日：2023-03-07

    申请号：US16774796

    申请日：2020-01-28

    Applicant: Snap Inc.

    Inventor： Zehao Xue ,  Zhou Ren

    IPC: G06K9/62 ,  G06N20/00 ,  G06V20/68

    Abstract: Systems and methods are provided for analyzing, by a computing device, location data associated with a location of the computing device to determine that an image or video captured using a messaging application on the computing device is captured near a food-related venue or event, receiving input related to food associated with the food-related venue or event, sending the image or video and the input related to food associated with the food-related venue or event to a computing system to train a machine learning model for food detection, and updating the messaging application to comprise the trained machine learning model for food detection.

    3D HAND SHAPE AND POSE ESTIMATION
    8.
    发明申请
    3D HAND SHAPE AND POSE ESTIMATION 有权

    公开(公告)号：US20220414985A1

    公开(公告)日：2022-12-29

    申请号：US17823764

    申请日：2022-08-31

    Applicant: Snap Inc.

    Inventor： Liuhao Ge ,  Zhou Ren ,  Yuncheng Li ,  Zehao Xue ,  Yingying Wang

    IPC: G06T17/20 ,  G06T7/73 ,  G06N3/08 ,  G06N3/04

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for receiving a monocular image that includes a depiction of a hand and extracting features of the monocular image using a plurality of machine learning techniques. The program and method further include modeling, based on the extracted features, a pose of the hand depicted in the monocular image by adjusting skeletal joint positions of a three-dimensional (3D) hand mesh using a trained graph convolutional neural network (CNN); modeling, based on the extracted features, a shape of the hand in the monocular image by adjusting blend shape values of the 3D hand mesh representing surface features of the hand depicted in the monocular image using the trained graph CNN; and generating, for display, the 3D hand mesh adjusted to model the pose and shape of the hand depicted in the monocular image.

    3D HAND SHAPE AND POSE ESTIMATION
    9.
    发明申请
    3D HAND SHAPE AND POSE ESTIMATION 有权

    公开(公告)号：US20210225077A1

    公开(公告)日：2021-07-22

    申请号：US17222176

    申请日：2021-04-05

    Applicant: Snap Inc.

    Inventor： Liuhao Ge ,  Zhou Ren ,  Yuncheng LI ,  Zehao Xue ,  Yingying Wang

    IPC: G06T17/20 ,  G06T7/73 ,  G06N3/08 ,  G06N3/04

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for receiving a monocular image that includes a depiction of a hand and extracting features of the monocular image using a plurality of machine learning techniques. The program and method further include modeling, based on the extracted features, a pose of the hand depicted in the monocular image by adjusting skeletal joint positions of a three-dimensional (3D) hand mesh using a trained graph convolutional neural network (CNN); modeling, based on the extracted features, a shape of the hand in the monocular image by adjusting blend shape values of the 3D hand mesh representing surface features of the hand depicted in the monocular image using the trained graph CNN; and generating, for display, the 3D hand mesh adjusted to model the pose and shape of the hand depicted in the monocular image.

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