Abstract
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.
Abstract (translated)
物体检测在自动驾驶中扮演着关键角色，因为准确且高效地在快速移动的场景中检测物体至关重要。传统的基于帧的相机在平衡延迟和带宽方面面临挑战，需要采取创新解决方案。事件相机因低延迟、高动态范围和低功耗而成为自动驾驶的有前景的传感器。然而，有效地利用异步和稀疏事件数据存在挑战，特别是在维持低延迟和轻量架构进行物体检测方面。本文对使用事件数据进行物体检测在自动驾驶中的概述，展示了事件相机的竞争优势。
URL
https://arxiv.org/abs/2405.03995
