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    TRAINING INSTANCE SEGMENTATION NEURAL NETWORKS THROUGH CONTRASTIVE LEARNING
    11.
    发明公开
    TRAINING INSTANCE SEGMENTATION NEURAL NETWORKS THROUGH CONTRASTIVE LEARNING 审中-公开

    公开(公告)号：US20230334842A1

    公开(公告)日：2023-10-19

    申请号：US18136252

    申请日：2023-04-18

    Applicant: Waymo LLC

    Inventor： Alex Zihao Zhu ,  Vincent Michael Casser ,  Henrik Kretzschmar ,  Reza Mahjourian ,  Soeren Pirk

    IPC: G06V10/82 ,  G06V10/774

    CPC classification number: G06V10/82 ,  G06V10/774

    Abstract: Methods, systems, and apparatus for processing inputs that include video frames using neural networks. In one aspect, a system comprises one or more computers configured to obtain a set of one or more training images and, for each training image, ground truth instance data that identifies, for each of one or more object instances, a corresponding region of the training image that depicts the object instance. For each training image in the set, the one or more computers process the training image using an instance segmentation neural network to generate an embedding output comprising a respective embedding for each of a plurality of output pixels. The one or more computers then train the instance segmentation neural network to minimize a loss function.

    TIME-LINE BASED OBJECT TRACKING ANNOTATION
    12.
    发明申请
    TIME-LINE BASED OBJECT TRACKING ANNOTATION 有权

    公开(公告)号：US20220358314A1

    公开(公告)日：2022-11-10

    申请号：US17314925

    申请日：2021-05-07

    Applicant: Waymo LLC

    Inventor： Yulai Shen ,  Henrik Kretzschmar ,  Jeffrey Sham ,  Jeffrey Carlson ,  Lo Po Tsui ,  Dragomir Anguelov

    IPC: G06K9/00 ,  G06K9/32 ,  G06N20/00

    Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for generating and editing object track labels for objects detected in video data. One of the methods includes obtaining a video segment comprising multiple image frames associated with multiple time points; obtaining object track data specifying a set of object tracks; providing, for presentation to a user, a user interface for modifying the object track data, the user interface displaying object timeline representations of the object tracks; receiving one or more user inputs that indicate one or more modifications to the object timeline representations; updating the object timeline representations displayed in the timeline display area; and updating the object track data according to the updated object timeline representations.

    Generating Environmental Data
    13.
    发明申请
    Generating Environmental Data 有权

    公开(公告)号：US20210150799A1

    公开(公告)日：2021-05-20

    申请号：US17098943

    申请日：2020-11-16

    Applicant: Waymo LLC

    Inventor： Zhenpei Yang ,  Yuning Chai ,  Yin Zhou ,  Pei Sun ,  Henrik Kretzschmar ,  Sean Rafferty ,  Dumitru Erhan ,  Dragomir Anguelov

    IPC: G06T15/04 ,  G06T9/00 ,  G06T7/70 ,  G06N3/04 ,  G06N3/08 ,  B60W60/00 ,  B60W30/095 ,  B60W50/06

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generated simulated sensor data. One of the methods includes obtaining a surfel map generated from sensor observations of a real-world environment and generating, for each surfel in the surfel map, a respective grid having a plurality of grid cells, wherein each grid has an orientation matching an orientation of a corresponding surfel, and wherein each grid cell within each grid is assigned a respective color value. For a simulated location within a simulated representation of the real-world environment, a textured surfel rendering is generated, including combining color information from grid cells visible from the simulated location within the simulated representation of the real-world environment.

    LONG-RANGE OBJECT DETECTION, LOCALIZATION, TRACKING AND CLASSIFICATION FOR AUTONOMOUS VEHICLES
    14.
    发明申请
    LONG-RANGE OBJECT DETECTION, LOCALIZATION, TRACKING AND CLASSIFICATION FOR AUTONOMOUS VEHICLES 有权

    公开(公告)号：US20250014357A1

    公开(公告)日：2025-01-09

    申请号：US18892711

    申请日：2024-09-23

    Applicant: Waymo LLC

    Inventor： Ruichi Yu ,  Kang Li ,  Tao Han ,  Robert Cosgriff ,  Henrik Kretzschmar

    IPC: G06V20/58 ,  G01S13/931 ,  G01S17/931 ,  G06F18/22

    Abstract: Aspects of the disclosure relate to controlling a vehicle. For instance, using a camera, a first camera image including a first object may be captured. A first bounding box for the first object and a distance to the first object may be identified. A second camera image including a second object may be captured. A second bounding box for the second image and a distance to the second object may be identified. Whether the first object is the second object may be determined using a plurality of models to compare visual similarity of the two bounding boxes, to compare a three-dimensional location based on the distance to the first object and a three-dimensional location based on the distance to the second object, and to compare results from the first and second models. The vehicle may be controlled in an autonomous driving mode based on a result of the third model.

    Phrase recognition model for autonomous vehicles
    18.
    发明授权
    Phrase recognition model for autonomous vehicles 有权

    公开(公告)号：US10902272B2

    公开(公告)日：2021-01-26

    申请号：US16879299

    申请日：2020-05-20

    Applicant: Waymo LLC

    Inventor： Victoria Dean ,  Abhijit S. Ogale ,  Henrik Kretzschmar ,  David Harrison Silver ,  Carl Kershaw ,  Pankaj Chaudhari ,  Chen Wu ,  Congcong Li

    IPC: G06K9/00 ,  G05D1/00 ,  G06N3/08 ,  G06T11/20 ,  G06F40/30 ,  G06K9/34

    Abstract: Aspects of the disclosure relate to training and using a phrase recognition model to identify phrases in images. As an example, a selected phrase list may include a plurality of phrases is received. Each phrase of the plurality of phrases includes text. An initial plurality of images may be received. A training image set may be selected from the initial plurality of images by identifying the phrase-containing images that include one or more phrases from the selected phrase list. Each given phrase-containing image of the training image set may be labeled with information identifying the one or more phrases from the selected phrase list included in the given phrase-containing images. The model may be trained based on the training image set such that the model is configured to, in response to receiving an input image, output data indicating whether a phrase of the plurality of phrases is included in the input image.

    PHRASE RECOGNITION MODEL FOR AUTONOMOUS VEHICLES
    19.
    发明申请
    PHRASE RECOGNITION MODEL FOR AUTONOMOUS VEHICLES 审中-公开

    公开(公告)号：US20190392231A1

    公开(公告)日：2019-12-26

    申请号：US16018490

    申请日：2018-06-26

    Applicant: Waymo LLC

    Inventor： Victoria Dean ,  Abhijit S. Ogale ,  Henrik Kretzschmar ,  David Harrison Silver ,  Carl Kershaw ,  Pankaj Chaudhari ,  Chen Wu ,  Congcong Li

    IPC: G06K9/00 ,  G05D1/00 ,  G06N3/08 ,  G06F17/27 ,  G06K9/34 ,  G06T11/20

    Abstract: Aspects of the disclosure relate to training and using a phrase recognition model to identify phrases in images. As an example, a selected phrase list may include a plurality of phrases is received. Each phrase of the plurality of phrases includes text. An initial plurality of images may be received. A training image set may be selected from the initial plurality of images by identifying the phrase-containing images that include one or more phrases from the selected phrase list. Each given phrase-containing image of the training image set may be labeled with information identifying the one or more phrases from the selected phrase list included in the given phrase-containing images. The model may be trained based on the training image set such that the model is configured to, in response to receiving an input image, output data indicating whether a phrase of the plurality of phrases is included in the input image.

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