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公开(公告)号：US20230027813A1
公开(公告)日：2023-01-26
申请号：US17936570
申请日：2022-09-29
Inventor： Xipeng YANG , Xiao TAN , Hao SUN , Errui DING
Abstract: An object detecting method includes: obtaining an object image of an object; obtaining an object feature map by performing feature extraction on the object image; obtaining decoded features by performing feature mapping on the object feature map by adopting a mapping network of an object recognition model; obtaining positions of prediction boxes by inputting the decoded features into a first prediction layer of the object recognition model to perform object regression prediction; and obtaining classes of objects within the prediction boxes by inputting the decoded features into a second prediction layer of the object recognition model to perform object class prediction.
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2.发明申请公开(公告)号：US20210272306A1
公开(公告)日：2021-09-02
申请号：US17324174
申请日：2021-05-19
Inventor： Minyue JIANG , Xipeng YANG , Xiao TAN , Hao SUN
Abstract: The present application discloses a method for training an image depth estimation model, a method and apparatus for processing image depth information, an automatic driving vehicle, an electronic device, a program product, a storage medium, which includes: inputting a sample environmental image, sample environmental point cloud data and sample edge information of the sample environmental image into a to-be-trained model; and determining initial depth information of each of pixel points in the sample environmental image and a feature relationship between each of the pixel points and a corresponding neighboring pixel point of each of the pixel points through the to-be-trained model, and optimizing the initial depth information of each of the pixel points according to the feature relationship to obtain optimized depth information of each of the pixel points, and adjusting a parameter of the to-be-trained model according to the optimized depth information to obtain the image depth estimation model.
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