IMAGE FACE MANIPULATION
    21.
    发明申请

    公开(公告)号:US20210295020A1

    公开(公告)日:2021-09-23

    申请号:US17303871

    申请日:2021-06-09

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for synthesizing a realistic image with a new expression of a face in an input image by receiving an input image comprising a face having a first expression; obtaining a target expression for the face; and extracting a texture of the face and a shape of the face. The program and method for generating, based on the extracted texture of the face, a target texture corresponding to the obtained target expression using a first machine learning technique; generating, based on the extracted shape of the face, a target shape corresponding to the obtained target expression using a second machine learning technique; and combining the generated target texture and generated target shape into an output image comprising the face having a second expression corresponding to the obtained target expression.

    AVATAR STYLE TRANSFORMATION USING NEURAL NETWORKS

    公开(公告)号:US20210104087A1

    公开(公告)日:2021-04-08

    申请号:US17247557

    申请日:2020-12-16

    Applicant: Snap Inc.

    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.

    Region-based stabilized face tracking

    公开(公告)号:US10949648B1

    公开(公告)日:2021-03-16

    申请号:US16170997

    申请日:2018-10-25

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing at least one program and a method for accessing a set of images depicting at least a portion of a face. A set of facial regions of the face is identified, each facial region of the set of facial regions intersecting another facial region with at least one common vertex which is a member of a set of facial vertices. For each facial region of the set of facial regions, a weight formed from a set of region coefficients is generated. Based on the set of facial regions and the weight of each facial region of the set of facial regions, the face is tracked across the set of images.

    Avatar style transformation using neural networks

    公开(公告)号:US10896534B1

    公开(公告)日:2021-01-19

    申请号:US16135911

    申请日:2018-09-19

    Applicant: Snap Inc.

    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.

    Avatar style transformation using neural networks

    公开(公告)号:US11348301B2

    公开(公告)日:2022-05-31

    申请号:US17247557

    申请日:2020-12-16

    Applicant: Snap Inc.

    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.

    Object modeling using light projection

    公开(公告)号:US11164376B1

    公开(公告)日:2021-11-02

    申请号:US16116590

    申请日:2018-08-29

    Applicant: Snap Inc.

    Abstract: A shape generation system can generate a three-dimensional (3D) model of an object from a two-dimensional (2D) image of the object by projecting vectors onto light cones created from the 2D image. The projected vectors can be used to more accurately create the 3D model of the object based on image element (e.g., pixel) values of the image.

    Image face manipulation
    30.
    发明授权

    公开(公告)号:US11055514B1

    公开(公告)日:2021-07-06

    申请号:US16220859

    申请日:2018-12-14

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for synthesizing a realistic image with a new expression of a face in an input image by receiving an input image comprising a face having a first expression; obtaining a target expression for the face; and extracting a texture of the face and a shape of the face. The program and method for generating, based on the extracted texture of the face, a target texture corresponding to the obtained target expression using a first machine learning technique; generating, based on the extracted shape of the face, a target shape corresponding to the obtained target expression using a second machine learning technique; and combining the generated target texture and generated target shape into an output image comprising the face having a second expression corresponding to the obtained target expression.

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