Skip to main content


Multi-robot, Multi-Sensor, Multi-Environment Event Dataset

Updates #

  • 2023/08/06: The code used to process M3ED has been released in the Github repo. All the h5 data files have been reprocessed to include the version attribute with the corresponding commit hash. We also improved the Data Overview section with a better description of the folder structure and the data files.
  • 2023/07/27: M3ED Rev. 1.1 was released! This version includes several updates and fixes: fixed GT odometry relative to local map for long sequences, improved density of GT depth, improved semantic segmentation reprojection and add visualizations of the data. Additionally, a few sequences have been added.
  • 2023/06/19: M3ED Rev. 1.0 was released at the CVPR 2023 Workshop on Event-based Vision ­čÄë!

Overview #

M3ED provides high-quality synchronized and labeled data from multiple platforms, including wheeled ground vehicles, legged robots, and aerial robots, operating in challenging conditions such as driving along off-road trails, navigating through dense forests, and executing aggressive flight maneuvers.

M3ED processed data, raw data, and code are available to download. Check out our Github repo for an overview on how the data is processed.

Mentions #

License #

M3ED is released under the Attribution-ShareAlike 4.0 International (CC BY-SA 4.0). You are allowed to share and adapt under the condition that you give the appropriate credit, indicate if changes were made, and distribute your contributions under the same license.

Read the paper #

You can access the paper from the CVPRW Proceedings.

    author    = {Chaney, Kenneth and Cladera, Fernando and Wang, Ziyun and Bisulco, Anthony and Hsieh, M. Ani and Korpela, Christopher and Kumar, Vijay and Taylor, Camillo J. and Daniilidis, Kostas},
    title     = {M3ED: Multi-Robot, Multi-Sensor, Multi-Environment Event Dataset},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
    month     = {June},
    year      = {2023},
    pages     = {4015-4022}