ShadowScout: Robust Unsupervised Shadow Detection for RGB Imagery

Estephan Rustom, Henrique Cabral, Sreeraj Rajendran, Elena Tsiporkova

2025

Abstract

Accurate shadow detection and correction are critical for improving image classification and segmentation but remain challenging due to the lack of well-labeled datasets and the context-specific nature of shadows, which limit the generalizability of supervised models. Existing unsupervised approaches, on the other hand, often require specialized data or are computationally intensive due to high parameterization. In this paper, we introduce ShadowScout, a novel, low-parameterized, unsupervised deep learning method for shadow detection using standard RGB images. ShadowScout is fast, achieves performance comparable to state-of-the-art supervised methods, and surpasses existing unsupervised techniques across various datasets. Additionally, the model can seamlessly incorporate extra data, such as near-infrared channels, to enhance shadow detection accuracy further. ShadowScout is available on the authors’ GitHub repository (https://github.com/EluciDATALab/elucidatalab.starterkits/tree/ main/models/shadows).

Paper Citation

in Harvard Style

Rustom E., Cabral H., Rajendran S. and Tsiporkova E. (2025). ShadowScout: Robust Unsupervised Shadow Detection for RGB Imagery. 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 657-668. DOI: 10.5220/0013254900003912

in Bibtex Style

@conference{visapp25,
author={Estephan Rustom and Henrique Cabral and Sreeraj Rajendran and Elena Tsiporkova},
title={ShadowScout: Robust Unsupervised Shadow Detection for RGB Imagery},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2025},
pages={657-668},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013254900003912},
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 - ShadowScout: Robust Unsupervised Shadow Detection for RGB Imagery
SN - 978-989-758-728-3
AU - Rustom E.
AU - Cabral H.
AU - Rajendran S.
AU - Tsiporkova E.
PY - 2025
SP - 657
EP - 668
DO - 10.5220/0013254900003912
PB - SciTePress