PADetBench: Towards benchmarking texture- and patch-based physical attacks against object detection

Jiawei Lian, Jianhong Pan, Lefan Wang, Yi Wang, Shaohui Mei, Lap-Pui Chau

Abstract: Highlights•Comprehensive Benchmark Framework: We present the first large-scale benchmark integrating 23 physical attack methods and 48 object detection models, enabling systematic comparative analysis.•Realistic Simulation Environment: Our framework accurately models physical dynamics and cross-domain transformations, balancing reproducibility with practical relevance.•Extensive Empirical Analysis: Over 8,000 evaluations reveal critical insights into detector vulnerabilities and attack limitations.•Open-Source Infrastructure: Our end-to-end pipeline, with publicly available code and datasets, provides a foundation for future research in AI security.

External IDs:doi:10.1016/j.knosys.2025.114395