VIDEO QUESTION ANSWERING
    8.
    发明申请

    公开(公告)号:WO2022271266A1

    公开(公告)日:2022-12-29

    申请号:PCT/US2022/026349

    申请日:2022-04-26

    Abstract: Implementations are described herein for formulating natural language descriptions based on temporal sequences of digital images. In various implementations, a natural language input may be analyzed. Based on the analysis, a semantic scope to be imposed on a natural language description that is to be formulated based on a temporal sequence of digital images may be determined. The temporal sequence of digital images may be processed based on one or more machine learning models to identify one or more candidate features that fall within the semantic scope. One or more other features that fall outside of the semantic scope may be disregarded. The natural language description may be formulated to describe one or more of the candidate features.

    DETECTING OBJECTS IN A VIDEO USING ATTENTION MODELS

    公开(公告)号:WO2023282847A1

    公开(公告)日:2023-01-12

    申请号:PCT/SG2022/050344

    申请日:2022-05-24

    Applicant: LEMON INC.

    Abstract: The present disclosure describes techniques of detecting objects in a video. The techniques comprises extracting features from each frame of the video; generating a first attentive feature by applying a first attention model on at least some of features extracted from any particular frame among the plurality of frames, wherein the first attention model identifies correlations between a plurality of locations in the particular frame by computing relationships between any two locations among the plurality of locations; generating a second attentive feature by applying a second attention model on at least one pair of features at different levels selected from the features extracted from the particular frame, wherein the second attention model identifies a correlation between at least one pair of locations corresponding to the at least one pair of features; and generating a representation of an object included in the particular frame.

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