MODULATED IMAGE SEGMENTATION
    13.
    发明申请

    公开(公告)号:US20230135137A1

    公开(公告)日:2023-05-04

    申请号:US18090577

    申请日:2022-12-29

    Applicant: Snap Inc.

    Abstract: A modulated segmentation system can use a modulator network to emphasize spatial prior data of an object to track the object across multiple images. The modulated segmentation system can use a segmentation network that receives spatial prior data as intermediate data that improves segmentation accuracy. The segmentation network can further receive visual guide information from a visual guide network to increase tracking accuracy via segmentation.

    VIRTUAL OBJECT MACHINE LEARNING
    14.
    发明申请

    公开(公告)号:US20210271874A1

    公开(公告)日:2021-09-02

    申请号:US17322609

    申请日:2021-05-17

    Applicant: Snap Inc.

    Abstract: A machine learning scheme can be trained on a set of labeled training images of a subject in different poses, with different textures, and with different background environments. The label or marker data of the subject may be stored as metadata to a 3D model of the subject or rendered images of the subject. The machine learning scheme may be implemented as a supervised learning scheme that can automatically identify the labeled data to create a classification model. The classification model can classify a depicted subject in many different environments and arrangements (e.g., poses).

    Modulated image segmentation
    17.
    发明授权

    公开(公告)号:US11551059B1

    公开(公告)日:2023-01-10

    申请号:US16192457

    申请日:2018-11-15

    Applicant: Snap Inc.

    Abstract: A modulated segmentation system can use a modulator network to emphasize spatial prior data of an object to track the object across multiple images. The modulated segmentation system can use a segmentation network that receives spatial prior data as intermediate data that improves segmentation accuracy. The segmentation network can further receive visual guide information from a visual guide network to increase tracking accuracy via segmentation.

    Neural networks for facial modeling

    公开(公告)号:US11100311B2

    公开(公告)日:2021-08-24

    申请号:US16509083

    申请日:2019-07-11

    Applicant: Snap Inc.

    Abstract: Systems, devices, media, and methods are presented for modeling facial representations using image segmentation with a client device. The systems and methods receive an image depicting a face, detect at least a portion of the face within the image, and identify a set of facial features within the portion of the face. The systems and methods generate a descriptor function representing the set of facial features, fit object functions of the descriptor function, identify an identification probability for each facial feature, and assign an identification to each facial feature.

    Virtual object machine learning
    19.
    发明授权

    公开(公告)号:US10579869B1

    公开(公告)日:2020-03-03

    申请号:US15653186

    申请日:2017-07-18

    Applicant: Snap Inc.

    Abstract: A machine learning scheme can be trained on a set of labeled training images of a subject in different poses, with different textures, and with different background environments. The label or marker data of the subject may be stored as metadata to a 3D model of the subject or rendered images of the subject. The machine learning scheme may be implemented as a supervised learning scheme that can automatically identify the labeled data to create a classification model. The classification model can classify a depicted subject in many different environments and arrangements (e.g., poses).

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