Official implementation of the DOC-Depth method.

If you use our method in your research, please cite :

@inproceedings{deMoreau2024doc,
  title = {DOC-Depth: A novel approach for dense depth ground truth generation},
  author = {De Moreau, Simon and Corsia, Mathias and Bouchiba, Hassan and Almehio, Yasser and Bursuc, Andrei and El-Idrissi, Hafid and Moutarde, Fabien},
  booktitle = {2025 IEEE Intelligent Vehicles Symposium (IV)},
  year = {2025},
}

Please visit our project page to download the dense annotations of KITTI.

The first step of the pipeline is to calibrate together LiDAR and Camera. See the Calibration folder to use our tool.

The easiest way to record your dataset is to use ROS to record all your sensors into ".bag" files.

After recording, you must use our pre-processing pipeline with SLAM and DOC to obtain a dense and classified reconstruction of your record. See the Preprocessing folder for more informations.

Finally, you can use our tool to apply our composite rendering to the classified LiDAR frames and obtain your dense depth. See the Rendering folder to access our tool.

This repository is licensed under the Apache License 2.0.