@inproceedings{0f4ef829d277459480934c41017eb458,
title = "DurLAR: A High-Fidelity 128-Channel LiDAR Dataset with Panoramic Ambient and Reflectivity Imagery for Multi-Modal Autonomous Driving Applications",
keywords = "autonomous driving, dataset, dense depth, flash LiDAR, ground truth depth, high resolution LiDAR, monocular depth estimation, stereo vision, three dimensional",
author = "Li Li and Ismail, {Khalid N.} and Shum, {Hubert P.H.} and Breckon, {Toby P.}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 9th International Conference on 3D Vision, 3DV 2021 ; Conference date: 01-12-2021 Through 03-12-2021",
year = "2021",
doi = "10.1109/3DV53792.2021.00130",
language = "English",
series = "Proceedings - 2021 International Conference on 3D Vision, 3DV 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1227--1237",
booktitle = "Proceedings - 2021 International Conference on 3D Vision, 3DV 2021",
}