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arXiv · 2506.21909

CERBERUS: Crack Evaluation & Recognition Benchmark for Engineering Reliability & Urban Stability

Justin Reinman·Sunwoong Choi
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Abstract

CERBERUS is a synthetic benchmark designed to help train and evaluate AI models for detecting cracks and other defects in infrastructure. It includes a crack image generator and realistic 3D inspection scenarios built in Unity. The benchmark features two types of setups: a simple Fly-By wall inspection and a more complex Underpass scene with lighting and geometry challenges. We tested a popular object detection model (YOLO) using different combinations of synthetic and real crack data. Results show that combining synthetic and real data improves performance on real-world images. CERBERUS provides a flexible, repeatable way to test defect detection systems and supports future research in automated infrastructure inspection. CERBERUS is publicly available at https://github.com/justinreinman/Cerberus-Defect-Generator.

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Justin Reinman, Sunwoong Choi. 2025-06-27. CERBERUS: Crack Evaluation & Recognition Benchmark for Engineering Reliability & Urban Stability. https://arxiv.org/abs/2506.21909

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