Object detection plays a critical role in autonomous driving, where accurately and efficiently detecting objects in fast-moving scenes is crucial. Traditional frame-based cameras face challenges in balancing latency and bandwidth, necessitating the need for innovative solutions. Event cameras have emerged as promising sensors for autonomous driving due to their low latency, high dynamic range, and low power consumption. However, effectively utilizing the asynchronous and sparse event data presents challenges, particularly in maintaining low latency and lightweight architectures for object detection. This paper provides an overview of object detection using event data in autonomous driving, showcasing the competitive benefits of event cameras.

翻译：目标检测在自动驾驶中发挥着关键作用，准确高效地检测快速移动场景中的目标至关重要。传统帧相机在平衡延迟与带宽方面面临挑战，亟需创新解决方案。事件相机凭借低延迟、高动态范围和低功耗等优势，已成为自动驾驶领域极具前景的传感器。然而，如何有效利用异步稀疏的事件数据仍存在挑战，尤其在需要保持低延迟和轻量级架构的目标检测任务中。本文系统综述了基于事件数据的自动驾驶目标检测技术，展示了事件相机的竞争性优势。