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Found 4 papers, 4 papers with code
CSE: Surface Anomaly Detection with Contrastively Selected Embedding
Detecting surface anomalies of industrial materials poses a significant challenge within a myriad of industrial manufacturing processes.
Ranked #2 on
Anomaly Detection
on MVTEC AD textures
Distillation-based fabric anomaly detection
Given the extensive variability in colors, textures, and defect types, fabric defect detection poses a complex and challenging problem in the field of patterned textures inspection.
FABLE : Fabric Anomaly Detection Automation Process
In this paper, we propose an automation process for industrial fabric texture defect detection with a specificity-learning process during the domain-generalized anomaly detection.
MixedTeacher : Knowledge Distillation for fast inference textural anomaly detection
For a very long time, unsupervised learning for anomaly detection has been at the heart of image processing research and a stepping stone for high performance industrial automation process.
Ranked #2 on
Anomaly Detection
on MVTEC AD textures
