公开(公告)号：US11804043B2

公开(公告)日：2023-10-31

申请号：US17348181

申请日：2021-06-15

Applicant: Lemon Inc.

Inventor： Xiaojie Jin ,  Yi-Wen Chen ,  Xiaohui Shen

IPC: G06K9/00 ,  G06V20/40 ,  G06V10/46 ,  G06F18/214

CPC classification number: G06V20/41 ,  G06F18/214 ,  G06V10/462 ,  G06V2201/07

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.

公开(公告)号：US20220398402A1

公开(公告)日：2022-12-15

申请号：US17348181

申请日：2021-06-15

Applicant: Lemon Inc.

Inventor： Xiaojie JIN ,  Yi-Wen Chen ,  Xiaohui Shen

IPC: G06K9/00 ,  G06K9/46 ,  G06K9/62

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.