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l3ad

Tasks:
Robotics
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Tags:
CARLA
Robotics
autonomous-driving
end-to-end-driving
multi-modal
123D
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metadata 
license: mit
task_categories:
  - robotics
tags:
  - CARLA
  - Robotics
  - autonomous-driving
  - end-to-end-driving
  - multi-modal
  - 123D
pretty_name: LEAD 123D
size_categories:
  - 1K<n<10K

123D

LEAD 123D

Five hours of CARLA expert driving logs in the unified 123D Apache Arrow format.

Project · Code · py123d

Overview

LEAD 123D is a CARLA Leaderboard 2.0 driving dataset collected with LEAD's rule-based privileged expert and stored in the 123D unified driving-data format. Each route is a self-contained directory of Apache Arrow IPC files, one per modality.

Data structure

File Content
ego_state_se3.arrow Ego vehicle pose, velocity, acceleration
camera.pcam_{f,b,l,r}{0,1}.arrow RGB camera streams (front, back, left, right)
lidar.lidar_top.arrow Top LiDAR point clouds
box_detections_se3.arrow 3D bounding boxes for all dynamic actors
traffic_light_detections.arrow Per-frame traffic light states
sync.arrow Cross-modality synchronization timestamps
maps/carla/*.arrow HD map: lanes, intersections, crosswalks, road edges, road lines (WKB geometry)
  • Coordinate conventions: ISO 8855 (vehicle / body), OpenCV (cameras)

Usage

Install py123d and pull the dataset:

pip install py123d

git lfs install
git clone https://huggingface.co/datasets/ln2697/lead123d

See the py123d documentation for loading, visualization, and Scene/Map API usage.

License

Released under the MIT License. CARLA assets and OpenDRIVE maps remain under their respective upstream licenses.

Citation

If you use LEAD 123D, please cite the papers:

@inproceedings{Nguyen2026CVPR,
  author    = {Long Nguyen and Micha Fauth and Bernhard Jaeger and Daniel Dauner and
               Maximilian Igl and Andreas Geiger and Kashyap Chitta},
  title     = {LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2026},
}

@software{Contributors123D,
  title   = {123D: A Unified Library for Multi-Modal Autonomous Driving Data},
  author  = {123D Contributors},
  year    = {2026},
  url     = {https://github.com/kesai-labs/py123d},
  license = {Apache-2.0}
}