AD Dataset

AD datasets, primarily exemplified by the MVTec AD dataset and its 3D extension, are crucial for benchmarking unsupervised anomaly detection methods in industrial visual inspection. Current research focuses on improving model efficiency (e.g., through quantization and lightweight architectures like dual-branch reconstruction networks) and exploring effective pre-training strategies (including synthetic data like fractals), aiming to reduce reliance on large, labeled datasets. These advancements are significant for real-world applications, enabling faster, more resource-efficient anomaly detection in manufacturing and other domains where real-time performance and data scarcity are critical challenges.