BIDIRECTIONAL PAIRING ARCHITECTURE FOR OBJECT DETECTION IN VIDEO

    公开(公告)号:US20210209368A1

    公开(公告)日:2021-07-08

    申请号:US17059968

    申请日:2018-12-18

    Abstract: Techniques related to training and implementing a bidirectional pairing architecture for object detection are discussed. Such techniques include generating a first enhanced feature map for each frame of a video sequence by processing the frames in a first direction, generating a second enhanced feature map for frame by processing the frames in a second direction opposite the first, and determining object detection information for each frame using the first and second enhanced feature map for the frame.

    BIDIRECTIONAL PAIRING ARCHITECTURE FOR OBJECT DETECTION IN VIDEO

    公开(公告)号:US20220270366A1

    公开(公告)日:2022-08-25

    申请号:US17742122

    申请日:2022-05-11

    Abstract: Techniques related to training and implementing a bidirectional pairing architecture for object detection are discussed. Such techniques include generating a first enhanced feature map for each frame of a video sequence by processing the frames in a first direction, generating a second enhanced feature map for frame by processing the frames in a second direction opposite the first, and determining object detection information for each frame using the first and second enhanced feature map for the frame.

    POINT CLOUD BASED 3D SEMANTIC SEGMENTATION

    公开(公告)号:US20210303912A1

    公开(公告)日:2021-09-30

    申请号:US16828987

    申请日:2020-03-25

    Abstract: System and techniques are provided for three-dimension (3D) semantic segmentation. A device for 3D semantic segmentation includes: an interface, to obtain a point cloud data set for a time-ordered sequence of 3D frames, the 3D frames including a current 3D frame and one or more historical 3D frames previous to the current 3D frame; and processing circuitry, to: invoke a first artificial neural network (ANN) to estimate a 3D scene flow field for each of the one or more historical 3D frames by taking the current 3D frame as a reference frame; and invoke a second ANN to: produce an aggregated feature map, based on the reference frame and the estimated 3D scene flow field for each of the one or more historical 3D frames; and perform the 3D semantic segmentation based on the aggregated feature map.

Patent Agency Ranking