Explaining Spatial Relation Detection using Layerwise Relevance Propagation

Gabriel Farrugia; Adrian Muscat

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Paper

Explaining Spatial Relation Detection using Layerwise Relevance Propagation

Topics: Deep Learning for Visual Understanding ; Machine Learning Technologies for Vision; Vision for Robotics

In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, 378-385, 2020 , Valletta, Malta

Authors: Gabriel Farrugia and Adrian Muscat

Affiliation: University of Malta, Msida MSD 2080, Malta

Keyword(s): Spatial Relation Detection, Layerwise Relevance Propagation, Neural Networks, XAI.

Abstract: In computer vision, learning to detect relationships between objects is an important way to thoroughly understand images. Machine Learning models have been developed in this area. However, in critical scenarios where a simple decision is not enough, reasons to back up each decision are required and reliability comes into play. We investigate the role that geometric, language and depth features play in the task of predicting Spatial Relations by generating feature relevance measures using Layerwise Relevance Propagation. We carry out the evaluation of feature contributions on a per-class basis.

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Paper citation in several formats:

Farrugia, G. and Muscat, A. (2020). Explaining Spatial Relation Detection using Layerwise Relevance Propagation. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP; ISBN 978-989-758-402-2; ISSN 2184-4321, SciTePress, pages 378-385. DOI: 10.5220/0008964003780385

@conference{visapp20,
author={Gabriel Farrugia. and Adrian Muscat.},
title={Explaining Spatial Relation Detection using Layerwise Relevance Propagation},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP},
year={2020},
pages={378-385},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008964003780385},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP
TI - Explaining Spatial Relation Detection using Layerwise Relevance Propagation
SN - 978-989-758-402-2
IS - 2184-4321
AU - Farrugia, G.
AU - Muscat, A.
PY - 2020
SP - 378
EP - 385
DO - 10.5220/0008964003780385
PB - SciTePress