ROCVLGAug 27, 2024

Panoptic Perception for Autonomous Driving: A Survey

arXiv:2408.15388v17 citationsh-index: 3
Originality Synthesis-oriented
AI Analysis

It addresses the need for unified perception frameworks in autonomous driving, but is incremental as a survey rather than new research.

This survey reviews panoptic perception models in autonomous driving, comparing their performance, responsiveness, and resource utilization to provide a detailed reference for researchers.

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.

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