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公开(公告)号：US20210390407A1
公开(公告)日：2021-12-16
申请号：US17344254
申请日：2021-06-10
Applicant: Waymo LLC
Inventor： Vincent Michael Casser , Yuning Chai , Dragomir Anguelov , Hang Zhao , Henrik Kretzschmar , Reza Mahjourian , Anelia Angelova , Ariel Gordon , Soeren Pirk
Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for training a perspective computer vision model. The model is configured to receive input data characterizing an input scene in an environment from an input viewpoint and to process the input data in accordance with a set of model parameters to generate an output perspective representation of the scene from the input viewpoint. The system trains the model based on first data characterizing a scene in the environment from a first viewpoint and second data characterizing the scene in the environment from a second, different viewpoint.
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公开(公告)号：US20220335624A1
公开(公告)日：2022-10-20
申请号：US17721288
申请日：2022-04-14
Applicant: Waymo LLC
Inventor： Daniel Rudolf Maurer , Austin Charles Stone , Alper Ayvaci , Anelia Angelova , Rico Jonschkowski
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network to predict optical flow. One of the methods includes obtaining a batch of one or more training image pairs; for each of the pairs: processing the first training image and the second training image using the neural network to generate a final optical flow estimate; generating a cropped final optical flow estimate from the final optical flow estimate; and training the neural network using the cropped optical flow estimate.
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公开(公告)号：US12229972B2
公开(公告)日：2025-02-18
申请号：US17721288
申请日：2022-04-14
Applicant: Waymo LLC
Inventor： Daniel Rudolf Maurer , Austin Charles Stone , Alper Ayvaci , Anelia Angelova , Rico Jonschkowski
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network to predict optical flow. One of the methods includes obtaining a batch of one or more training image pairs; for each of the pairs: processing the first training image and the second training image using the neural network to generate a final optical flow estimate; generating a cropped final optical flow estimate from the final optical flow estimate; and training the neural network using the cropped optical flow estimate.
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公开(公告)号：US20230035454A1
公开(公告)日：2023-02-02
申请号：US17384637
申请日：2021-07-23
Applicant: Waymo LLC
Inventor： Daniel Rudolf Maurer , Alper Ayvaci , Robert William Anderson , Rico Jonschkowski , Austin Charles Stone , Anelia Angelova , Nichola Abdo , Christopher John Sweeney
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an optical flow label from a lidar point cloud. One of the methods includes obtaining data specifying a training example, including a first image of a scene in an environment captured at a first time point and a second image of the scene in the environment captured at a second time point. For each of a plurality of lidar points, a respective second corresponding pixel in the second image is obtained and a respective velocity estimate for the lidar point at the second time point is obtained. A respective first corresponding pixel in the first image is determined using the velocity estimate for the lidar point. A proxy optical flow ground truth for the training example is generated based on an estimate of optical flow of the pixel between the first and second images.
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