PIXEL DEPTH DETERMINATION FOR OBJECT
    23.
    发明公开

    公开(公告)号:US20230316666A1

    公开(公告)日:2023-10-05

    申请号:US17842006

    申请日:2022-06-16

    Applicant: Snap Inc.

    CPC classification number: G06T19/006 G06V10/70 G06V10/26 G06V20/20 G06N20/20

    Abstract: Methods and systems are disclosed for performing operations for applying augmented reality elements to a person depicted in an image. The operations include receiving an image that includes data representing a depiction of a person; extracting a portion of the image; applying a first machine learning model stage to the portion to predict a depth of a point of interest for the data representing the depiction of the person; applying a second machine learning model stage to the portion of the image to predict a relative depth of each pixel in the portion of the image to the predicted depth of the point of interest; generating dense depth reconstruction of the data representing the depiction of the person based on outputs of the first and second stages of the machine learning model; and applying one or more AR elements to the image based on the dense depth reconstruction.

    DEFORMING REAL-WORLD OBJECT USING AN EXTERNAL MESH

    公开(公告)号:US20230090645A1

    公开(公告)日:2023-03-23

    申请号:US17448158

    申请日:2021-09-20

    Applicant: Snap Inc

    Abstract: Methods and systems are disclosed for performing operations comprising: receiving a video that includes a depiction of a real-world object; generating a three-dimensional (3D) body mesh associated with the real-world object that tracks movement of the real-world object across frames of the video; determining UV positions of the real-world object depicted in the video to obtain pixel values associated with the UV positions; generating an external mesh and associated augmented reality (AR) element representing the real-world object based on the pixel values associated with the UV positions; deforming the external mesh based on changes to the 3D body mesh and a deformation parameter; and modifying the video to replace the real-world object with the AR element based on the deformed external mesh.

    GENERATING THREE-DIMENSIONAL OBJECT MODELS FROM TWO-DIMENSIONAL IMAGES

    公开(公告)号:US20230070008A1

    公开(公告)日:2023-03-09

    申请号:US17760424

    申请日:2020-02-17

    Applicant: Snap Inc.

    Abstract: This specification discloses methods and systems for generating three-dimensional models of deformable objects from two-dimensional images. According to one aspect of this disclosure, there is described a computer implemented method for generating a three dimensional model of deformable object from a two-dimensional image. The method comprises: receiving, as input to an embedding neural network, the two-dimensional image, wherein the two dimensional image comprises an image of an object; generating, using the embedding neural network, an embedded representation of a two-dimensional image; inputting the embedded representation into a learned decoder model; and generating, using the learned decoder model, parameters of the three dimensional model of the object from the embedded representation.

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