@inproceedings{673da4c2ba47428f82627ac620b098df,
title = "It's All Around You: Range-Guided Cylindrical Network for 3D Object Detection",
abstract = "Modern perception systems in the field of autonomous driving rely on 3D data analysis. LiDAR sensors are frequently used to acquire such data due to their increased resilience to different lighting conditions. Although rotating LiDAR scanners produce ring-shaped patterns in space, most networks analyze their data using an orthogonal voxel sampling strategy. This work presents a novel approach for analyzing 3D data produced by 360-degree depth scanners, utilizing a more suitable coordinate system, which is aligned with the scanning pattern. Furthermore, we intro-duce a novel notion of range-guided convolutions, adapting the receptive field by distance from the ego vehicle and the object's scale. Our network demonstrates powerful results on the competitive nuScenes 3D object detection challenge, comparable to current state-of-the-art architectures.",
author = "Meytal Rapoport-Lavie and Dan Raviv",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 18th IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021 ; Conference date: 11-10-2021 Through 17-10-2021",
year = "2021",
doi = "10.1109/ICCVW54120.2021.00334",
language = "الإنجليزيّة",
series = "Proceedings of the IEEE International Conference on Computer Vision",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2992--3001",
booktitle = "Proceedings - 2021 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021",
address = "الولايات المتّحدة",
}