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公开(公告)号:US20220156483A1
公开(公告)日:2022-05-19
申请号:US17527653
申请日:2021-11-16
Applicant: Waymo LLC
Inventor: Pei Sun , Weiyue Wang , Yuning Chai , Xiao Zhang , Dragomir Anguelov
Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for performing object detection. The system obtains a respective range image corresponding to each point cloud in a set of point clouds captured by one or more sensors. The system processes each range image using a segmentation neural network to generate range image features and a segmentation output. The system generates a feature representation of the set of point clouds from only the feature representations of the foreground points. The system processes the feature representation of the set of point clouds using a prediction neural network to generate a prediction characterizing the set of point clouds.
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公开(公告)号:US12125298B2
公开(公告)日:2024-10-22
申请号:US17527653
申请日:2021-11-16
Applicant: Waymo LLC
Inventor: Pei Sun , Weiyue Wang , Yuning Chai , Xiao Zhang , Dragomir Anguelov
CPC classification number: G06V20/64 , G06T7/194 , G06T2207/10028 , G06T2207/20081 , G06T2207/20084
Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for performing object detection. The system obtains a respective range image corresponding to each point cloud in a set of point clouds captured by one or more sensors. The system processes each range image using a segmentation neural network to generate range image features and a segmentation output. The system generates a feature representation of the set of point clouds from only the feature representations of the foreground points. The system processes the feature representation of the set of point clouds using a prediction neural network to generate a prediction characterizing the set of point clouds.
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公开(公告)号:US20220156585A1
公开(公告)日:2022-05-19
申请号:US17526731
申请日:2021-11-15
Applicant: Waymo LLC
Inventor: Zhaoqi Leng , Shuyang Cheng , Weiyue Wang , Xiao Zhang , Dragomir Anguelov
Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for performing training of a neural network that is configured to process a network input comprising a point cloud to generate a network output for a point cloud processing task. The system obtains a set of labeled training examples and a set of unlabeled point clouds, generates a respective pseudo-label for each unlabeled point cloud, generates a plurality of pseudo-elements based on the respective pseudo-label for the unlabeled point cloud, generates augmented training data by augmenting the labeled training examples using the pseudo-elements generated for the unlabeled point clouds, and performing training of the neural network on the augmented training data.
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公开(公告)号:US11941875B2
公开(公告)日:2024-03-26
申请号:US17443674
申请日:2021-07-27
Applicant: Waymo LLC
Inventor: Yuning Chai , Pei Sun , Jiquan Ngiam , Weiyue Wang , Vijay Vasudevan , Benjamin James Caine , Xiao Zhang , Dragomir Anguelov
IPC: G06V20/00 , G01S7/48 , G01S17/89 , G06F18/21 , G06F18/213 , G06F18/25 , G06N3/08 , G06T7/70 , G06V10/94 , H04N23/10
CPC classification number: G06V20/00 , G01S7/4802 , G01S17/89 , G06F18/213 , G06F18/217 , G06F18/253 , G06N3/08 , G06T3/4046 , G06T7/70 , G06V10/95 , H04N23/10 , G06T2207/20084
Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for processing a perspective view range image generated from sensor measurements of an environment. The perspective view range image includes a plurality of pixels arranged in a two-dimensional grid and including, for each pixel, (i) features of one or more sensor measurements at a location in the environment corresponding to the pixel and (ii) geometry information comprising range features characterizing a range of the location in the environment corresponding to the pixel relative to the one or more sensors. The system processes the perspective view range image using a first neural network to generate an output feature representation. The first neural network comprises a first perspective point-set aggregation layer comprising a geometry-dependent kernel.
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