Panoptic Perception for Autonomous Driving: A Survey

Fuente: arXiv
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Autores principales: Li, Yunge, Xu, Lanyu
Formato: Preprint
Publicado: 2024
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author Li, Yunge
Xu, Lanyu
author_facet Li, Yunge
Xu, Lanyu
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2408_15388
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Panoptic Perception for Autonomous Driving: A Survey
Li, Yunge
Xu, Lanyu
Robotics
Computer Vision and Pattern Recognition
Machine Learning
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.
title Panoptic Perception for Autonomous Driving: A Survey
topic Robotics
Computer Vision and Pattern Recognition
Machine Learning
url https://arxiv.org/abs/2408.15388