Our autonomous vehicles are equipped with an in-house sensor suite that collects raw sensor data on other cars, pedestrians, traffic lights, and more. This dataset features the raw lidar and camera inputs collected by our autonomous fleet within a bounded geographic area. It includes:
0M
3D annotations.
0K
lidar point clouds.
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scenes at 60-90 minutes long.
Annotations provided by
Get a sense for how our lidars perceive the world around them with a top-down view of the data they collect.
Learn about perception for autonomous vehicles and the challenge of building systems designed to operate without human intervention.
Our example solution follows a single-shot, top-down, U-net neural network segmentation architecture that was trained on the lidar portion of the dataset. The rasterization uses the HD semantic map and projected lidar point cloud to show the state around the vehicle. You can use this example solution as a starting point for your own experimentation.
We use the familiar nuScenes format for our dataset to ensure compatibility with previous work. We’ve also customized the nuScenes devkit and included instructions on how to use it.
Citation instruction
If you use the dataset for scientific work, please cite the following:
@misc{
Woven Planet Holdings, Inc. 2019,
title = {Level 5 Perception Dataset 2020},
author = {Kesten, R. and Usman, M. and Houston, J. and Pandya, T. and Nadhamuni, K. and Ferreira, A. and Yuan, M. and Low, B. and Jain, A. and Ondruska, P. and Omari, S. and Shah, S. and Kulkarni, A. and Kazakova, A. and Tao, C. and Platinsky, L. and Jiang, W. and Shet, V.},
year = {2019},
howpublished = {\url{https://level-5.global/level5/data/}}
}Licensing information
The downloadable “Level 5 Perception Dataset” and included materials are ©2021 Woven Planet, Inc., and licensed under version 4.0 of the Creative Commons Attribution-NonCommercial-ShareAlike license (CC-BY-NC-SA-4.0
The HD map included with the dataset was developed using data from the OpenStreetMap database which is ©OpenStreetMap contributors and available under the ODbL-1.0 license.
The nuScenes devkit was previously published by nuTonomy under the Creative Commons Attribution-NonCommercial-ShareAlike license (CC-BY-NC-SA-4.0), but is currently published under the Apache license version 2.0. Lyft’s forked nuScenes devkit has been modified for use with the Lyft Level 5 AV dataset. Lyft’s modifications are ©2020 Lyft, Inc., and licensed under version 4.0 of the Creative Commons Attribution-NonCommercial-ShareAlike license (CC-BY-NC-SA-4.0).
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