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公开(公告)号：US11796670B2
公开(公告)日：2023-10-24
申请号：US17325762
申请日：2021-05-20
Inventor： Jin Fang , Dingfu Zhou , Xibin Song , Liangjun Zhang
Abstract: A radar point cloud data processing method and device, an apparatus, and storage medium are provided, which are related to technical fields of radar point cloud, automatic driving, and deep learning. An implementation includes: determining a target location area where a target object is located by utilizing a target detection box in the radar point cloud data; removing each point of the target object in the target location area from the radar point cloud data; and adding an object model to the target location area. By applying embodiments of the present disclosure, richer radar point cloud data may be obtained by removing the target object from the radar point cloud data and adding the needed three-dimensional model to the target location area in the radar point cloud data.
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公开(公告)号：US11288492B2
公开(公告)日：2022-03-29
申请号：US16773286
申请日：2020-01-27
Inventor： Xibin Song , Ruigang Yang
Abstract: The present disclosure provides a method and device for acquiring 3D information of an object. The method includes: extracting two-dimensional (2D) key points of the object based on the image, and determining a candidate 3D model set matching the image; determining a plurality of first reference attitudes and positions of each candidate 3D model according to the 3D key points and the 2D key points; acquiring a plurality of reprojection error values between each candidate 3D model and the object at the plurality of first reference attitudes and positions; determining a first target attitude and position and a first target 3D model corresponding to a minimum reprojection error value in the first reprojection error value set; and acquiring the 3D information of the object based on the first target attitude and position and the first target 3D model.
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公开(公告)号：US20210270958A1
公开(公告)日：2021-09-02
申请号：US17325762
申请日：2021-05-20
Inventor： Jin Fang , Dingfu Zhou , Xibin Song , Liangjun Zhang
Abstract: A radar point cloud data processing method and device, an apparatus, and storage medium are provided, which are related to technical fields of radar point cloud, automatic driving, and deep learning. An implementation includes: determining a target location area where a target object is located by utilizing a target detection box in the radar point cloud data; removing each point of the target object in the target location area from the radar point cloud data; and adding an object model to the target location area. By applying embodiments of the present disclosure, richer radar point cloud data may be obtained by removing the target object from the radar point cloud data and adding the needed three-dimensional model to the target location area in the radar point cloud data.
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公开(公告)号：US11841921B2
公开(公告)日：2023-12-12
申请号：US17112247
申请日：2020-12-04
Inventor： Xibin Song , Dingfu Zhou , Jin Fang , Liangjun Zhang
IPC: G06T7/50 , G06N20/00 , G06F18/214 , G06V10/42 , G06T3/40
CPC classification number: G06F18/214 , G06N20/00 , G06T3/40 , G06T7/50 , G06V10/42 , G06T2207/10028 , G06T2207/20081 , G06T2207/20084
Abstract: The present application provides a model training method and apparatus, and a prediction method and apparatus, and it relates to fields of artificial intelligence, deep learning, image processing, and autonomous driving. The model training method includes: inputting a first sample image of sample images into a depth information prediction model, and acquiring depth information of the first sample image; acquiring inter-image posture information based on a second sample image of the sample images and the first sample image; acquiring a projection image corresponding to the first sample image, at least according to the inter-image posture information and the depth information; and acquiring a loss function by determining a function for calculating a similarity between the second sample image and the projection image, and training the depth information prediction model using the loss function.
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