Data Format

scenario_xxx: sequence of sensor data
    |
    ----odometry:
    |    |
    |    ---odom_*.txt: pos_x, pos_y, pos_z, roll, pitch, yaw
    |
    ----label:
    |    |
    |    ---label2d_*.json: labels annotated in the camera space (labels, track_id, bbox, not_in_lidar, attributes, potential_destination)
        |    |
        |    ---label3d_*.txt: labels annotated in the pointcloud space (labels, track_id, stationary, pos_x, pos_y, pos_z, dim_x, dim_y, dim_z, yaw, vehicle_state, intended_actions, potential_destination,right turn/left turn/go forward/u turn/lane change not possible/none of the above)
    |
    ----pointcloud:
    |    |
    |    ---pc_*.ply: 360 deg pointcloud
    |
    ----image:
    |    |
    |    ---image_*.png: frontal-view image
    |
    ----map:
        |
        ---map.ply: map pointcloud

Download the dataset

The dataset is available for non-commercial usage. You must be affiliated with a university and use your university email address to make the request. Use this link to make the download request.

Citation

This dataset corresponds to the paper, LOKI: Long Term and Key Intentions for Trajectory Prediction, as it appears in the proceedings of International Conference on Computer Vision (ICCV 2021).

Please cite the following paper if you find this work useful:

@inproceedings{girase2021loki,
  title={LOKI: Long Term and Key Intentions for Trajectory Prediction},
  author={Girase, Harshayu and Gang, Haiming and Malla, Srikanth and Li, Jiachen and Kanehara, Akira and Mangalam, Karttikeya and Choi, Chiho},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={9803--9812},
  year={2021}
}