Panoptic Perception for Autonomous Driving: A Survey
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866914926925185024 |
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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 |