Panoptic perception represents a forefront advancement in autonomous driving technology, unifying multiple perception tasks into a singular, cohesive framework to facilitate a thorough understanding of the vehicle's surroundings. This survey reviews typical panoptic perception models for their unique inputs and architectures and compares them to performance, responsiveness, and resource utilization. It also delves into the prevailing challenges faced in panoptic perception and explores potential trajectories for future research. Our goal is to furnish researchers in autonomous driving with a detailed synopsis of panoptic perception, positioning this survey as a pivotal reference in the ever-evolving landscape of autonomous driving technologies.

翻译：全景感知代表了自动驾驶技术的前沿进展，它将多种感知任务统一到一个单一、连贯的框架中，以促进对车辆周围环境的全面理解。本综述回顾了典型全景感知模型的独特输入和架构，并在性能、响应性和资源利用方面对它们进行了比较。同时，本文深入探讨了全景感知当前面临的主要挑战，并探索了未来研究的潜在方向。我们的目标是为自动驾驶领域的研究人员提供一份关于全景感知的详细概述，使本综述成为自动驾驶技术不断发展的领域中的一个关键参考。