2 papers
cs.CV2024
Unsupervised Industrial Anomaly Detection via Pattern Generative and Contrastive Networks
Jianfeng Huang, Chenyang Li, Yimin Lin +1
It is hard to collect enough flaw images for training deep learning network in industrial production. Therefore, existing industrial anomaly detection methods prefer to use CNN-bas…
cs.CV2024
Patch-wise Auto-Encoder for Visual Anomaly Detection
Yajie Cui, Zhaoxiang Liu, Shiguo Lian
Anomaly detection without priors of the anomalies is challenging. In the field of unsupervised anomaly detection, traditional auto-encoder (AE) tends to fail based on the assumptio…