Anomaly detection is a crucial task across different domains and data types. However,
existing anomaly detection models are often designed for specific domains and modalities …

The vision-language model has brought great improvement to few-shot industrial anomaly
detection which usually needs to design of hundreds of prompts through prompt …

Visual Anomaly Detection (VAD) endeavors to pinpoint deviations from the concept of
normality in visual data, widely applied across diverse domains, eg, industrial defect …

Existing industrial visual anomaly detection models can be broadly categorized into two
paradigms, ie, the paradigm based on image reconstruction and the paradigm based on …

In this work, by re-examining the" matching" nature of Anomaly Detection (AD), we propose
a new AD framework that simultaneously enjoys new records of AD accuracy and …

Image reconstruction-based anomaly detection models are widely explored in industrial
visual inspection. However, existing models usually suffer from the trade-off between normal …

Industrial anomaly detection is an important task within computer vision with a wide range of
practical use cases. The small size of anomalous regions in many real-world datasets …

Anomaly detection is a challenging computer vision task in industrial scenario.
Advancements in deep learning constantly revolutionize vision-based anomaly detection …

Anomaly Detection is a relevant problem in numerous real-world applications especially
when dealing with images. However little attention has been paid to the issue of changes …

Quality inspection in the pharmaceutical and food industry is crucial to ensure that products
are safe for the customers. Among the properties that are controlled in the production …