Machine Vision-Based Object Detection for Autonomous Driving

Engineering notes

Key topics: autonomous driving, autonomous vehicle, object detection, 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

Vision-based perception is of great significance in autonomous driving, and object detection is one aspect of it. With the development of deep learning, research on machine vision algorithms has increasingly focused on deep learning methods, and these algorithms are widely applied to object detection in autonomous driving. Therefore, this paper provides a general review of vision-based object detection in the field of autonomous driving, especially those based on deep learning. Firstly, vision-based object detection algorithms are introduced. The application of these algorithms in autonomous vehicle object detection, including the integration and optimization of these algorithms for vehicle detection, pedestrian detection, and the recognition of traffic instructions, are discussed in the following section. Finally, the summary of existing challenges and outlook for the future are provided based on the current state of research.

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