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    Generating realistic point clouds
    23.
    发明授权
    Generating realistic point clouds 有权

    公开(公告)号：US11295517B2

    公开(公告)日：2022-04-05

    申请号：US17099589

    申请日：2020-11-16

    Applicant: Waymo LLC

    Inventor： Yin Zhou ,  Dragomir Anguelov ,  Zhangjie Cao

    IPC: G06T17/00 ,  G06N20/00 ,  G06K9/00 ,  G06N3/04

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating realistic full-scene point clouds. One of the methods includes obtaining an initial scene point cloud characterizing an initial scene in an environment; obtaining, for each of one or more objects, an object point cloud that characterizes the object; and processing a first input comprising the initial scene point cloud and the one or more object point clouds using a first neural network that is configured to process the first input to generate a final scene point cloud that characterizes a transformed scene that has the one or more objects added to the initial scene.

    Annotated surfel maps
    25.
    发明授权
    Annotated surfel maps 有权

    公开(公告)号：US11915490B2

    公开(公告)日：2024-02-27

    申请号：US17819883

    申请日：2022-08-15

    Applicant: Waymo LLC

    Inventor： Dragomir Anguelov ,  Colin Andrew Braley ,  Christoph Sprunk

    IPC: G06V20/56 ,  G06F18/214 ,  G06F18/2415

    CPC classification number: G06V20/56 ,  G06F18/214 ,  G06F18/2415

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for the generation and use of a surfel map with semantic labels. One of the methods includes receiving a surfel map that includes a plurality of surfels, wherein each surfel has associated data that includes one or more semantic labels; obtaining sensor data for one or more locations in the environment, the sensor data having been captured by one or more sensors of a first vehicle; determining one or more surfels corresponding to the one or more locations of the obtained sensor data; identifying one or more semantic labels for the one or more surfels corresponding to the one or more locations of the obtained sensor data; and performing, for each surfel corresponding to the one or more locations of the obtained sensor data, a label-specific detection process for the surfel.

    GENERATING REALISTIC POINT CLOUDS
    29.
    发明申请
    GENERATING REALISTIC POINT CLOUDS 有权

    公开(公告)号：US20220230387A1

    公开(公告)日：2022-07-21

    申请号：US17713108

    申请日：2022-04-04

    Applicant: Waymo LLC

    Inventor： Yin Zhou ,  Dragomir Anguelov ,  Zhangjie Cao

    IPC: G06T17/00 ,  G06N20/00 ,  G06N3/04 ,  G06V20/10

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating realistic full-scene point clouds. One of the methods includes obtaining an initial scene point cloud characterizing an initial scene in an environment; obtaining, for each of one or more objects, an object point cloud that characterizes the object;
    and processing a first input comprising the initial scene point cloud and the one or more object point clouds using a first neural network that is configured to process the first input to generate a final scene point cloud that characterizes a transformed scene that has the one or more objects added to the initial scene.

    MULTI-MODAL 3-D POSE ESTIMATION
    30.
    发明申请
    MULTI-MODAL 3-D POSE ESTIMATION 有权

    公开(公告)号：US20220156965A1

    公开(公告)日：2022-05-19

    申请号：US17505900

    申请日：2021-10-20

    Applicant: Waymo LLC

    Inventor： Jingxiao Zheng ,  Xinwei Shi ,  Alexander Gorban ,  Junhua Mao ,  Andre Liang Cornman ,  Yang Song ,  Ting Liu ,  Ruizhongtai Qi ,  Yin Zhou ,  Congcong Li ,  Dragomir Anguelov

    IPC: G06T7/73 ,  G06K9/62 ,  G06K9/00

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for estimating a 3-D pose of an object of interest from image and point cloud data. In one aspect, a method includes obtaining an image of an environment; obtaining a point cloud of a three-dimensional region of the environment; generating a fused representation of the image and the point cloud; and processing the fused representation using a pose estimation neural network and in accordance with current values of a plurality of pose estimation network parameters to generate a pose estimation network output that specifies, for each of multiple keypoints, a respective estimated position in the three-dimensional region of the environment.

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