Weakly Supervised Defect Detection
4 papers with code • 4 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Weakly Supervised Defect Detection
Most implemented papers
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows
However, current methods can not effectively map image features to a tractable base distribution and ignore the relationship between local and global features which are important to identify anomalies.
Mixed supervision for surface-defect detection: from weakly to fully supervised learning
We also show that mixed supervision with only a handful of fully annotated samples added to weakly labelled training images can result in performance comparable to the fully supervised model's performance but at a significantly lower annotation cost.
S2D2Net: An Improved Approach For Robust Steel Surface Defects Diagnosis With Small Sample Learning
Surface defect recognition of products is a necessary process to guarantee the quality of industrial production.
DSR -- A dual subspace re-projection network for surface anomaly detection
The state-of-the-art in discriminative unsupervised surface anomaly detection relies on external datasets for synthesizing anomaly-augmented training images.