21 citations · 43 across the 4 of their papers we have counts for
4 papers
Exploring Few-Shot Defect Segmentation in General Industrial Scenarios with Metric Learning and Vision Foundation Models
Tongkun Liu, Bing Li, Xiao Jin +3
Industrial defect segmentation is critical for manufacturing quality control. Due to the scarcity of training defect samples, few-shot semantic segmentation (FSS) holds significant…
FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly Detection
Tongkun Liu, Bing Li, Xiao Du +4
Image reconstruction-based anomaly detection models are widely explored in industrial visual inspection. However, existing models usually suffer from the trade-off between normal r…
Component-aware anomaly detection framework for adjustable and logical industrial visual inspection
Tongkun Liu, Bing Li, Xiao Du +4
Industrial visual inspection aims at detecting surface defects in products during the manufacturing process. Although existing anomaly detection models have shown great performance…
Reconstruction from edge image combined with color and gradient difference for industrial surface anomaly detection
Tongkun Liu, Bing Li, Zhuo Zhao +3
Reconstruction-based methods are widely explored in industrial visual anomaly detection. Such methods commonly require the model to well reconstruct the normal patterns but fail in…