Taming Generative Synthetic Data for X-Ray Prohibited Item Detection

This paper addresses the challenge of training prohibited item detection models for X-ray security screening, which normally requires large amounts of manually collected and labeled images. The authors propose Xsyn, a one-stage synthetic image generation pipeline using text-to-image generation (a type of AI that creates images from text descriptions) that automatically creates realistic X-ray security images without requiring labor-intensive manual image extraction and annotation.