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公开(公告)号:US20250037303A1
公开(公告)日:2025-01-30
申请号:US18614254
申请日:2024-03-22
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 , G06F18/214 , G06F18/25 , G06V20/58
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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公开(公告)号:US20240157979A1
公开(公告)日:2024-05-16
申请号:US18511710
申请日:2023-11-16
Applicant: Waymo LLC
Inventor: Chiyu Jiang , Andre Liang Cornman , Cheolho Park , Benjamin Sapp , Yin Zhou , Dragomir Anguelov
CPC classification number: B60W60/00276 , B60W50/0097 , B60W50/06 , B60W2552/20 , B60W2554/4044 , B60W2556/10
Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating trajectory predictions for one or more target agents, e.g., a vehicle, a cyclist, or a pedestrian, in an environment. In one aspect, one of the methods include: obtaining scene context data characterizing a scene at a current time point in an environment that includes multiple target agents; generating, from the scene context data, an encoded representation of the scene in the environment; and generating, by a diffusion model based on the encoded representation, a respective trajectory prediction output that predicts a respective future trajectory for each of the multiple target agents after the current time point.
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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
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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公开(公告)号:US20250121857A1
公开(公告)日:2025-04-17
申请号:US18913074
申请日:2024-10-11
Applicant: Waymo LLC
Inventor: Bertrand Robert Douillard , Aurick Qikun Zhou , Rami Al-Rfou , Kratarth Goel , Benjamin Sapp , Andre Liang Cornman , Cheolho Park , Lingyun Liu
Abstract: A method performed by one or more computers, the method comprising: obtaining scene context data characterizing a scene in an environment at a current time point, wherein the scene context data includes features of the scene in a scene-centric coordinate system; generating a scene-centric encoded representation of the scene in the environment by processing the scene context data using an encoder neural network; for each target agent: obtaining agent-specific features for the target agent, processing the agent-specific features for the target agent and the scene-centric encoded representation of the scene using a fusion neural network to generate a fused scene representation for the target agent, and processing the fused scene representation for the target agent using a decoder neural network to generate a trajectory prediction output for the target agent in an agent-centric coordinate system for the target agent.
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公开(公告)号:US11967103B2
公开(公告)日:2024-04-23
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 , G06F18/214 , G06F18/25 , G06V20/58
CPC classification number: G06T7/73 , G06F18/214 , G06F18/251 , G06V20/58 , G06T2207/10028 , G06T2207/20081 , G06T2207/20084 , G06T2207/30196 , G06T2207/30261
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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公开(公告)号:US20230072020A1
公开(公告)日:2023-03-09
申请号:US17940665
申请日:2022-09-08
Applicant: Waymo LLC
Inventor: Andre Liang Cornman , David Lee , Yang Song , Zijian Guo , Edward Stephen Walker, Jr. , Yuanfang Wang , Zhengli Zhao , Hsu-kuang Chiu
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for open vehicle doors prediction using a neural network model. One of the methods includes: obtaining sensor data (i) that includes a portion of a point cloud generated by a laser sensor of an autonomous vehicle and (ii) that characterizes a vehicle that is in a vicinity of the autonomous vehicle in an environment; and processing the sensor data using an open door prediction neural network to generate an open door prediction that predicts a likelihood score that the vehicle has an open door.
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