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公开(公告)号：US11544869B2
公开(公告)日：2023-01-03
申请号：US17342434
申请日：2021-06-08
Applicant: Waymo LLC
Inventor： Alper Ayvaci , Yu-Han Chen , Ruichi Yu , Chen Wu , Noha Waheed Ahmed Radwan , Jonathon Shlens
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating object interaction predictions using a neural network. One of the methods includes obtaining a sensor input derived from data generated by one or more sensors that characterizes a scene. The sensor input is provided to an object interaction neural network. The object interaction neural network is configured to process the sensor input to generate a plurality of object interaction outputs. Each respective object interaction output includes main object information and interacting object information. The respective object interaction outputs corresponding to the plurality of regions in the sensor input are received as output of the object interaction neural network.
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公开(公告)号：US20210012089A1
公开(公告)日：2021-01-14
申请号：US16923823
申请日：2020-07-08
Applicant: Waymo LLC
Inventor： Jonathon Shlens , Patrick An Phu Nguyen , Benjamin James Caine , Jiquan Ngiam , Wei Han , Brandon Chauloon Yang , Yuning Chai , Pei Sun , Yin Zhou , Xi Yi , Ouais Alsharif , Zhifeng Chen , Vijay Vasudevan
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing point cloud data representing a sensor measurement of a scene captured by one or more sensors to generate an object detection output that identifies locations of one or more objects in the scene. When deployed within an on-board system of a vehicle, the object detection output that is generated can be used to make autonomous driving decisions for the vehicle with enhanced accuracy.
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公开(公告)号：US12106528B2
公开(公告)日：2024-10-01
申请号：US17684334
申请日：2022-03-01
Applicant: Waymo LLC
Inventor： Nichola Abdo , Jonathon Shlens , Zhifeng Chen , Christopher John Sweeney , Philipp Florian Jund
IPC: G06T9/00 , G06F18/214
CPC classification number: G06T9/002 , G06F18/2148
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting scene flow. One of the methods includes obtaining a current point cloud representing an observed scene at a current time point; obtaining object label data that identifies a first three-dimensional region in the observed scene; determining, for each current three-dimensional point that is within the first three-dimensional region and using the object label data, a respective preceding position of the current three-dimensional point at a preceding time point in a reference frame of the sensor at the current time point; and generating, using the preceding positions, a scene flow label for the current point cloud that comprises a respective ground truth motion vector for each of a plurality of the current three-dimensional points.
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公开(公告)号：US20220319054A1
公开(公告)日：2022-10-06
申请号：US17684334
申请日：2022-03-01
Applicant: Waymo LLC
Inventor： Nichola Abdo , Jonathon Shlens , Zhifeng Chen , Christopher John Sweeney , Philipp Florian Jund
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting scene flow. One of the methods includes obtaining a current point cloud representing an observed scene at a current time point; obtaining object label data that identifies a first three-dimensional region in the observed scene; determining, for each current three-dimensional point that is within the first three-dimensional region and using the object label data, a respective preceding position of the current three-dimensional point at a preceding time point in a reference frame of the sensor at the current time point; and generating, using the preceding positions, a scene flow label for the current point cloud that comprises a respective ground truth motion vector for each of a plurality of the current three-dimensional points.
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Patent Agency Ranking
公开(公告)号：US11043003B2
公开(公告)日：2021-06-22
申请号：US16686840
申请日：2019-11-18
Applicant: Waymo LLC
Inventor： Alper Ayvaci , Yu-Han Chen , Ruichi Yu , Chen Wu , Noha Waheed Ahmed Radwan , Jonathon Shlens
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating object interaction predictions using a neural network. One of the methods includes obtaining a sensor input derived from data generated by one or more sensors that characterizes a scene. The sensor input is provided to an object interaction neural network. The object interaction neural network is configured to process the sensor input to generate a plurality of object interaction outputs. Each respective object interaction output includes main object information and interacting object information. The respective object interaction outputs corresponding to the plurality of regions in the sensor input are received as output of the object interaction neural network.
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公开(公告)号：US20210295555A1
公开(公告)日：2021-09-23
申请号：US17342434
申请日：2021-06-08
Applicant: Waymo LLC
Inventor： Alper Ayvaci , Yu-Han Chen , Ruichi Yu , Chen Wu , Noha Waheed Ahmed Radwan , Jonathon Shlens
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating object interaction predictions using a neural network. One of the methods includes obtaining a sensor input derived from data generated by one or more sensors that characterizes a scene. The sensor input is provided to an object interaction neural network. The object interaction neural network is configured to process the sensor input to generate a plurality of object interaction outputs. Each respective object interaction output includes main object information and interacting object information. The respective object interaction outputs corresponding to the plurality of regions in the sensor input are received as output of the object interaction neural network.
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公开(公告)号：US20210150752A1
公开(公告)日：2021-05-20
申请号：US16686840
申请日：2019-11-18
Applicant: Waymo LLC
Inventor： Alper Ayvaci , Yu-Han Chen , Ruichi Yu , Chen Wu , Noha Waheed Ahmed Radwan , Jonathon Shlens
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating object interaction predictions using a neural network. One of the methods includes obtaining a sensor input derived from data generated by one or more sensors that characterizes a scene. The sensor input is provided to an object interaction neural network. The object interaction neural network is configured to process the sensor input to generate a plurality of object interaction outputs. Each respective object interaction output includes main object information and interacting object information. The respective object interaction outputs corresponding to the plurality of regions in the sensor input are received as output of the object interaction neural network.
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公开(公告)号：US11450120B2
公开(公告)日：2022-09-20
申请号：US16923823
申请日：2020-07-08
Applicant: Waymo LLC
Inventor： Jonathon Shlens , Patrick An Phu Nguyen , Benjamin James Caine , Jiquan Ngiam , Wei Han , Brandon Chauloon Yang , Yuning Chai , Pei Sun , Yin Zhou , Xi Yi , Ouais Alsharif , Zhifeng Chen , Vijay Vasudevan
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing point cloud data representing a sensor measurement of a scene captured by one or more sensors to generate an object detection output that identifies locations of one or more objects in the scene. When deployed within an on-board system of a vehicle, the object detection output that is generated can be used to make autonomous driving decisions for the vehicle with enhanced accuracy.
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公开(公告)号：US20210334651A1
公开(公告)日：2021-10-28
申请号：US17194115
申请日：2021-03-05
Applicant: Waymo LLC
Inventor： Zhaoqi Leng , Ekin Dogus Cubuk , Barret Zoph , Jiquan Ngiam , Congcong Li , Jonathon Shlens , Shuyang Cheng
IPC: G06N3/08 , G06F17/18 , G06K9/62 , G01S17/894
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training a machine learning model to perform a machine learning task by processing input data to the model. For example, the input data can include image, video, or point cloud data, and the task can be a perception task such as classification or detection task. In one aspect, the method includes receiving training data including a plurality of training inputs; receiving a plurality of data augmentation policy parameters that define different transformation operations for transforming training inputs before the training inputs are used to train the machine learning model; maintaining a plurality of candidate machine learning models; for each of the plurality of candidate machine learning models: repeatedly determining an augmented batch of training data; training the candidate machine learning model using the augmented batch of the training data; and updating the maintained data.
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