SEQUENCE-OF-SEQUENCES MODEL FOR 3D OBJECT RECOGNITION

    公开(公告)号:US20230034794A1

    公开(公告)日:2023-02-02

    申请号:US17878591

    申请日:2022-08-01

    Applicant: Snap Inc.

    Abstract: Systems and methods are disclosed for capturing multiple sequences of views of a three-dimensional object using a plurality of virtual cameras. The systems and methods generate aligned sequences from the multiple sequences based on an arrangement of the plurality of virtual cameras in relation to the three-dimensional object. Using a convolutional network, the systems and methods classify the three-dimensional object based on the aligned sequences and identify the three-dimensional object using the classification.

    Sequence-of-sequences model for 3D object recognition

    公开(公告)号:US11410439B2

    公开(公告)日:2022-08-09

    申请号:US16870138

    申请日:2020-05-08

    Applicant: Snap Inc.

    Abstract: Systems and methods are disclosed for capturing multiple sequences of views of a three-dimensional object using a plurality of virtual cameras. The systems and methods generate aligned sequences from the multiple sequences based on an arrangement of the plurality of virtual cameras in relation to the three-dimensional object. Using a convolutional network, the systems and methods classify the three-dimensional object based on the aligned sequences and identify the three-dimensional object using the classification.

    SEGMENT ACTION DETECTION
    5.
    发明申请

    公开(公告)号:US20210407548A1

    公开(公告)日:2021-12-30

    申请号:US17465001

    申请日:2021-09-02

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a storage medium storing a program and method for receiving a video comprising a plurality of video segments; selecting a target action sequence that includes a sequence of action phases; receiving features of each of the video segments; computing, based on the received features, for each of the plurality of video segments, a plurality of action phase confidence scores indicating a likelihood that a given video segment includes a given action phase of the sequence of action phases; identifying a set of consecutive video segments of the plurality of video segments that corresponds to the target action sequence, wherein video segments in the set of consecutive video segments are arranged according to the sequence of action phases; and generating a display of the video that includes the set of consecutive video segments and skips other video segments in the video.

    Segment action detection
    7.
    发明授权

    公开(公告)号:US11704893B2

    公开(公告)日:2023-07-18

    申请号:US17465001

    申请日:2021-09-02

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a storage medium storing a program and method for receiving a video comprising a plurality of video segments; selecting a target action sequence that includes a sequence of action phases; receiving features of each of the video segments; computing, based on the received features, for each of the plurality of video segments, a plurality of action phase confidence scores indicating a likelihood that a given video segment includes a given action phase of the sequence of action phases; identifying a set of consecutive video segments of the plurality of video segments that corresponds to the target action sequence, wherein video segments in the set of consecutive video segments are arranged according to the sequence of action phases; and generating a display of the video that includes the set of consecutive video segments and skips other video segments in the video.

    Segment action detection
    8.
    发明授权

    公开(公告)号:US11158351B1

    公开(公告)日:2021-10-26

    申请号:US16228120

    申请日:2018-12-20

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a storage medium storing a program and method for receiving a video comprising a plurality of video segments; selecting a target action sequence that includes a sequence of action phases; receiving features of each of the video segments; computing, based on the received features, for each of the plurality of video segments, a plurality of action phase confidence scores indicating a likelihood that a given video segment includes a given action phase of the sequence of action phases; identifying a set of consecutive video segments of the plurality of video segments that corresponds to the target action sequence, wherein video segments in the set of consecutive video segments are arranged according to the sequence of action phases; and generating a display of the video that includes the set of consecutive video segments and skips other video segments in the video.

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