Image anomaly detection plays a pivotal role in industrial inspection. Traditional approaches
often demand distinct models for specific categories, resulting in substantial deployment …

Unsupervised visual anomaly localization research has garnered significant attention in
industrial component surface quality inspection tasks, particularly in realistic scenarios …

The unsupervised detection and localization of image anomalies hold significant importance
across various domains, particularly in industrial quality inspection. Despite its widespread …

Visual anomaly detection plays a crucial role in manufacturing to ensure product quality by
identifying image patterns that deviate from the expected ones. Existing methods that rely on …

As one of the typical means of anomaly detection, unsupervised reconstruction-based
anomaly detection methods usually extract the normal representations and utilize the …

Unsupervised anomaly detection methods can identify surface defects in industrial images
by leveraging only normal samples for training. Due to the risk of overfitting when learning …

Anomaly detection has an important impact on the development of industry. How to detect
anomalies based on industrial data is an important research hotspot. At present, most …

Detecting anomalies utilizing time series data is critical in various real-world applications for
ensuring personal safety and preventing financial losses. Deep-learning methods have …