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公开(公告)号:US20250022257A1
公开(公告)日:2025-01-16
申请号:US18687024
申请日:2022-09-07
Applicant: 42DOT INC.
Inventor: Seong Gyun JEONG , Hee Yeon KWON , Seok Woo JUNG
IPC: G06V10/774 , B60W40/06 , G06V10/762 , G06V10/776 , G06V10/82 , G06V20/56
Abstract: The present disclosure relates to a method and device for generating a lane polyline by using a neural network model.
The method according to an embodiment of the present disclosure may include generating a bird's-eye-view feature based on a base image obtained from at least one sensor mounted on a vehicle, and training a neural network model by using the bird's-eye-view feature as input data for the neural network model and using a lane polyline for a certain road as output data. In the present disclosure, a lane polyline obtained from the above-described neural network model may be used for controlling the vehicle without performing a separate process on the lane polyline.-
公开(公告)号:US20240078817A1
公开(公告)日:2024-03-07
申请号:US18458163
申请日:2023-08-30
Applicant: 42DOT INC.
Inventor: Seok Woo JUNG , Hee Yeon KWON , Jung Hee KIM , Seong Gyun JEONG
CPC classification number: G06V20/588 , B60W30/12 , G06V10/82
Abstract: The present disclosure relates to a method and apparatus for generating a lane polyline by using a neural network model. The method according to an embodiment may extract a multi-scale image feature by using a base image obtained from at least one sensor loaded in a vehicle. According to the method, the multi-scale image feature is input to a first neural network model as input data and a BEV feature may be obtained as output data from the first neural network model. Also, according to the method, the BEV feature may be input to a second neural network model as input data and a polyline image with respect to a certain road may be obtained as output data from the second neural network model. In the present disclosure, a lane polyline obtained from the neural network may be utilized in vehicle control without going through an additional treatment process.
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