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Authors: Álvaro Ramajo-Ballester ; Arturo de la Escalera Hueso and José María Armingol Moreno

Affiliation: Intelligent Systems Lab, University Carlos III de Madrid, Spain

Keyword(s): 3D Object Detection, Autonomous Driving, Deep Learning.

Abstract: Autonomous driving has been one of the most promising research lines in the last decade. Although still far off the sought-after level 5, the research community shows great advancements in one of the most challenging tasks: the 3d perception. The rapid progress of related fields like Deep Learning is one the reasons behind this success. This enables and improves the processing algorithms for the input data provided by LiDAR, cameras, radars and such other devices used for environment perception. With such growing knowledge, reviewing and structuring the state-of-the-art solutions becomes a necessity in order to correctly address future research directions. This paper provides a comprehensive survey of the progress of 3D object detection in terms of sensor data, available datasets, top-performing architectures and most notable frameworks that serve as a baseline for current and upcoming works.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Ramajo-Ballester, Á.; de la Escalera Hueso, A. and Armingol Moreno, J. (2023). 3D Object Detection for Autonomous Driving: A Practical Survey. In Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-652-1; ISSN 2184-495X, SciTePress, pages 64-73. DOI: 10.5220/0011748400003479

@conference{vehits23,
author={Álvaro Ramajo{-}Ballester. and Arturo {de la Escalera Hueso}. and José María {Armingol Moreno}.},
title={3D Object Detection for Autonomous Driving: A Practical Survey},
booktitle={Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2023},
pages={64-73},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011748400003479},
isbn={978-989-758-652-1},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - 3D Object Detection for Autonomous Driving: A Practical Survey
SN - 978-989-758-652-1
IS - 2184-495X
AU - Ramajo-Ballester, Á.
AU - de la Escalera Hueso, A.
AU - Armingol Moreno, J.
PY - 2023
SP - 64
EP - 73
DO - 10.5220/0011748400003479
PB - SciTePress