Autonomous driving paper index
A Review of the Development of BEV Perception Algorithms for Autonomous Driving Applications
One-line summary
An autonomous driving research paper: A Review of the Development of BEV Perception Algorithms for Autonomous Driving Applications.
Engineering notes
Key topics: autonomous driving, bev perception, bev, perception. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
: With the advancement of driver assistance technology and intelligent vehicle technology, navigation-assisted driving (NOA) technology has become a popular research and development and commercially sought-after technology hotspot in the automotive industry in order to make driving easier and more convenient when driving on urban roads.NOA is an automated driving technology that enables vehicles to drive on urban roads automatically with the help of high-precision navigation technology and automated driving technology, and its emergence is attributed to the development and progress of BEV technology solutions. The rise of NOA is due to the development and advancement of BEV technology, which can unify multimodal data into a single feature space in the automatic driving perception task module, and has better development potential than other perception learning models. This paper focuses on the application and importance of BEV perceptual algorithms in autonomous driving, and also analyses the challenges faced by BEV perceptual algorithms in complex and dynamic traffic environments.
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