Environment Setup and Model Benchmark of the MuFoRa Dataset

Islam Fadl, Torsten Schön, Valentino Behret, Thomas Brandmeier, Frank Palme, Thomas Helmer

2025

Abstract

Adverse meteorological conditions, particularly fog and rain, present significant challenges to computer vision algorithms and autonomous systems. This work presents MuFoRa a novel, controllable, and measured multimodal dataset recorded at CARISSMA’s indoor test facility, specifically designed to assess perceptual difficulties in foggy and rainy environments. The dataset bridges research gap in the public benchmarking datasets, where quantifiable weather parameters are lacking. The proposed dataset comprises synchronized data from two sensor modalities: RGB stereo cameras and LiDAR sensors, captured under varying intensities of fog and rain. The dataset incorporates synchronized meteorological annotations, such as visibility through fog and precipitation levels of rain, and the study contributes a detailed explanation of the diverse weather effects observed during data collection in the methods section. The dataset’s utility is demonstrated through a baseline evaluation example, assessing the performance degradation of state-of-the-art YOLO11 and DETR 2D object detection algorithms under controlled and quantifiable adverse weather conditions. The public release of the dataset (https://doi.org/10.5281/zenodo.14175611) facilitates various benchmarking and quanti- tative assessments of advanced multimodal computer vision and deep learning models under the challenging conditions of fog and rain.

Paper Citation

in Harvard Style

Fadl I., Schön T., Behret V., Brandmeier T., Palme F. and Helmer T. (2025). Environment Setup and Model Benchmark of the MuFoRa Dataset. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 729-737. DOI: 10.5220/0013307900003912

in Bibtex Style

@conference{visapp25,
author={Islam Fadl and Torsten Schön and Valentino Behret and Thomas Brandmeier and Frank Palme and Thomas Helmer},
title={Environment Setup and Model Benchmark of the MuFoRa Dataset},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2025},
pages={729-737},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013307900003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Environment Setup and Model Benchmark of the MuFoRa Dataset
SN - 978-989-758-728-3
AU - Fadl I.
AU - Schön T.
AU - Behret V.
AU - Brandmeier T.
AU - Palme F.
AU - Helmer T.
PY - 2025
SP - 729
EP - 737
DO - 10.5220/0013307900003912
PB - SciTePress