The comprehensive intelligent development of the manufacturing industry puts forward new
requirements for the quality inspection of industrial products. This paper summarizes the …

Currently, deep learning-based visual inspection has been highly successful with the help of
supervised learning methods. However, in real industrial scenarios, the scarcity of defect …

The recent rapid development of deep learning has laid a milestone in industrial image
anomaly detection (IAD). In this paper, we provide a comprehensive review of deep learning …

Unsupervised anomaly segmentation methods based on knowledge distillation have
recently been developed and have shown superior segmentation performance. However …

Anomaly detection is an important problem for recent advances in machine learning. To this
end, many attempts have emerged to detect unknown anomalies of the images by learning …

Traditional methods of visual anomaly detection based on reconstruction often use normal
data to train autoencoder. Then the metric distance detection method is used to estimate …

Advancements in computer vision have fueled rapid developments in unsupervised
anomaly detection, but current methods often encounter limitations when addressing …

With the development of deep learning, abnormal detection methods have been widely
presented to improve performances in various applications, including visual inspection …

Recently, significant performance improvements have been achieved in deep learning-
based anomaly detection methods by introducing large neural network architectures and …

Reconstruction-based anomaly detections with convolutional autoencoders (CAEs) have
been commonly used for unsupervised anomaly detection. The task of anomaly …