CSE: Surface Anomaly Detection with Contrastively Selected Embedding

arXiv:2403.01859v1 Announce Type: new
Abstract: Detecting surface anomalies of industrial materials poses a significant challenge within a myriad of industrial manufacturing processes. In recent times, various methodologies have emerged, capitalizing on the advantages of employing a network pre-trained on natural images for the extraction of representative features. Subsequently, these features are subjected to processing through a diverse range of techniques including memory banks, normalizing flow, and knowledge distillation, which have exhibited exceptional accuracy. This paper revisits approaches based on pre-trained …

abstract advantages anomaly anomaly detection arxiv challenge cs.cv detection embedding extraction features images industrial industrial manufacturing manufacturing materials natural network processes surface type