ALICE-LRI Experiments

This repository contains all the code, scripts, and configuration required to reproduce the experiments for the ALICE-LRI paper. It is designed to provide a fully reproducible workflow, from data preparation to results and paper figures.

Reproducibility Guide

The complete step-by-step process to reproduce all experiments and results is described in detail in REPRODUCIBILITY.md.

Repository Structure

• alice-lri/: Submodule containing the ALICE-LRI library (core algorithm, C++/Python bindings).
• rtst-modified/: Fork of the original RTST compression algorithm, including both the original and modified versions for evaluation.
• container/: Container definition and environment files for reproducible builds (Apptainer/Singularity).
• results/: Databases, CSVs, and generated figures/tables from experiments.
• scripts/: Automation scripts for data preparation, experiment execution, and analysis.
• .env: Environment configuration file. This file defines important paths and variables for both local and HPC environments.

Related Repositories and Organization

• ALICE-LRI GitHub Organization: The main organization hosting the ALICE-LRI ecosystem and related projects.

• ALICE-LRI (core library): The main repository for the ALICE-LRI library. This is included here as the alice-lri/ subfolder.

• RTST-Modified: Fork of the original RTST compression algorithm, containing both the original and modified versions for evaluation. Included here as the rtst-modified/ subfolder.

Paper and Citation

The ALICE-LRI algorithm and experiments are described in our paper:

Title: ALICE-LRI: A General Method for Lossless Range Image Generation for Spinning LiDAR Sensors without Calibration Metadata
Authors: Samuel Soutullo, Miguel Yermo, David L. Vilariño, Óscar G. Lorenzo, José C. Cabaleiro, Francisco F. Rivera
Link: https://arxiv.org/abs/2510.20708

How to cite:

@misc{soutullo2025alicelri,
      title={ALICE-LRI: A General Method for Lossless Range Image Generation for Spinning LiDAR Sensors without Calibration Metadata}, 
      author={Samuel Soutullo and Miguel Yermo and David L. Vilariño and Óscar G. Lorenzo and José C. Cabaleiro and Francisco F. Rivera},
      year={2025},
      eprint={2510.20708},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2510.20708}, 
}

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For questions or issues, please refer to REPRODUCIBILITY.md or contact the corresponding author of the paper (Samuel Soutullo).