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    3D hand shape and pose estimation
    3.
    发明授权
    3D hand shape and pose estimation 有权

    公开(公告)号：US11468636B2

    公开(公告)日：2022-10-11

    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.

    3D hand shape and pose estimation
    4.
    发明授权
    3D hand shape and pose estimation 有权

    公开(公告)号：US10796482B2

    公开(公告)日：2020-10-06

    申请号：US16210927

    申请日：2018-12-05

    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.

    3D hand shape and pose estimation
    5.
    发明授权
    3D hand shape and pose estimation 有权

    公开(公告)号：US11734844B2

    公开(公告)日：2023-08-22

    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 ,  G06T7/50 ,  G06T7/73 ,  G06N3/08 ,  G06N3/045 ,  G06V10/774 ,  G06V10/82 ,  G06V40/10

    CPC classification number: G06T7/50 ,  G06N3/045 ,  G06N3/08 ,  G06T7/75 ,  G06T17/20 ,  G06V10/774 ,  G06V10/82 ,  G06V40/107 ,  G06T2207/10004

    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.

    AVATAR STYLE TRANSFORMATION USING NEURAL NETWORKS
    7.
    发明申请
    AVATAR STYLE TRANSFORMATION USING NEURAL NETWORKS 有权

    公开(公告)号：US20220254084A1

    公开(公告)日：2022-08-11

    申请号：US17724235

    申请日：2022-04-19

    Applicant: Snap Inc.

    Inventor： Harrison Jesse Smith ,  Chen Cao ,  Yingying Wang

    IPC: G06T13/40 ,  H04L51/10 ,  G06N3/08 ,  G06N20/00

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing at least one program and a method for transforming a motion style of an avatar from a first style to a second style. The program and method include: retrieving, by a processor from a storage device, an avatar depicting motion in a first style; receiving user input selecting a second style; obtaining, based on the user input, a trained machine learning model that performs a non-linear transformation of motion from the first style to the second style; and applying the obtained trained machine learning model to the retrieved avatar to transform the avatar from depicting motion in the first style to depicting motion in the second style.

    3D hand shape and pose estimation
    8.
    发明授权
    3D hand shape and pose estimation 有权

    公开(公告)号：US10997787B2

    公开(公告)日：2021-05-04

    申请号：US17010256

    申请日：2020-09-02

    Applicant: Snap Inc.

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

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

    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
    10.
    发明申请
    3D HAND SHAPE AND POSE ESTIMATION 审中-公开

    公开(公告)号：US20200184721A1

    公开(公告)日：2020-06-11

    申请号：US16210927

    申请日：2018-12-05

    Applicant: Snap Inc.

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

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

    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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