论文标题
自动驾驶汽车中的对象检测：状态和开放挑战
Object Detection in Autonomous Vehicles: Status and Open Challenges
论文作者
论文摘要
对象检测是一项计算机视觉任务，已成为当今许多消费者应用程序的组成部分，例如监视和安全系统，移动文本识别以及MRI/CT扫描中诊断疾病。对象检测也是支持自动驾驶的关键组件之一。自动驾驶汽车依靠对周围环境的感知来确保安全和稳健的驾驶性能。该感知系统使用对象检测算法来准确确定车辆附近的行人，车辆，交通标志和障碍等物体。基于深度学习的对象探测器在实时查找和本地定位这些对象方面起着至关重要的作用。本文讨论了对象探测器中的最新技术，并将其集成到自动驾驶汽车中的开放挑战。
Object detection is a computer vision task that has become an integral part of many consumer applications today such as surveillance and security systems, mobile text recognition, and diagnosing diseases from MRI/CT scans. Object detection is also one of the critical components to support autonomous driving. Autonomous vehicles rely on the perception of their surroundings to ensure safe and robust driving performance. This perception system uses object detection algorithms to accurately determine objects such as pedestrians, vehicles, traffic signs, and barriers in the vehicle's vicinity. Deep learning-based object detectors play a vital role in finding and localizing these objects in real-time. This article discusses the state-of-the-art in object detectors and open challenges for their integration into autonomous vehicles.
