FIReStereo: Forest InfraRed Stereo Dataset for UAS Depth Perception in Visually Degraded Environments

Devansh Dhrafani*, Yifei Liu*, Andrew Jong, Ukcheol Shin, Yao He, Tyler Harp, Yaoyu Hu, Jean Oh, Sebastian Scherer

IEEE RA-L 2025

Paper | Project Page | Preprint

Download data

1. Obtain access keys by filling out a simple survey.
2. Paste the keys into download_data.py.

pip install minio tqdm
python download_data.py [--outdir] [--unzip] [--data]

• --data: default is all. Select:
  • depth for our stereo thermal & depth collection
  • thermal for the collection featuring prescribed fire and smoke
  • rosbags for LiDAR and IMU data
  • reconstruction for the reconstructed point clouds and trajectories from SLAM

Calibration file can be found in config/firestereo.yaml.

More details about each dataset sequence can be found in data_description.md.

Visualization tool

python browse_data.py [--dir] [--options] [--skip] [--align_contrast] [--process]

• --dir: path to single thermal/depth directory or directory containing (thermal) img_left,img_right
• --options: visualize thermal or depth
• --skip: skip every nth frame
• --process: apply 16-bit to 8-bit processing with minmax or firestereo
• Navigate with:
  • <- -> for left, right
  • [ ] for left by n, right by n
  • p for printing current frame number
  • d for delete current frame
  • l for display horizontal lines across stereo pair
  • esc for exit

Visualize the thermal images with our 16-bit to 8-bit converstion and pre-processing pipeline by running python browse_data.py with --process firestere option. This will apply the same processing pipeline as in the paper.

Stay tuned for dataloader, training scripts, and models.

Citation

If you find this work useful, please consider citing:

@article{firestereo,
  author={Dhrafani, Devansh and Liu, Yifei and Jong, Andrew and Shin, Ukcheol and He, Yao and Harp, Tyler and Hu, Yaoyu and Oh, Jean and Scherer, Sebastian},
  journal={IEEE Robotics and Automation Letters}, 
  title={FIReStereo: Forest InfraRed Stereo Dataset for UAS Depth Perception in Visually Degraded Environments}, 
  year={2025},
  volume={10},
  number={4},
  pages={3302-3309},
  doi={10.1109/LRA.2025.3536278}
}