We introduce a novel Interval Bound Propagation (IBP) approach for the formal verification of object detection models, specifically targeting the Intersection over Union (IoU) metric. The approach has been implemented in an open source code, named IBP IoU, compatible with popular abstract interpretation based verification tools. The resulting verifier is evaluated on landing approach runway detection and handwritten digit recognition case studies. Comparisons against a baseline (Vanilla IBP IoU) highlight the superior performance of IBP IoU in ensuring accuracy and stability, contributing to more secure and robust machine learning applications.
@article{arxiv.2403.08788,
title = {VerifIoU -- Robustness of Object Detection to Perturbations},
author = {Noémie Cohen and Mélanie Ducoffe and Ryma Boumazouza and Christophe Gabreau and Claire Pagetti and Xavier Pucel and Audrey Galametz},
journal= {arXiv preprint arXiv:2403.08788},
year = {2025}
}
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44th Digital Avionics Systems Conference (DASC), Sep 2025, Montreal, Canada