5 citations · 5 across the 5 of their papers we have counts for
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cs.CV2026
URA-Net: Uncertainty-Integrated Anomaly Perception and Restoration Attention Network for Unsupervised Anomaly Detection
Wei Luo, Peng Xing, Yunkang Cao +3
Unsupervised anomaly detection plays a pivotal role in industrial defect inspection and medical image analysis, with most methods relying on the reconstruction framework. However,…
cs.CV2025
3CAD: A Large-Scale Real-World 3C Product Dataset for Unsupervised Anomaly
Enquan Yang, Peng Xing, Hanyang Sun +4
Industrial anomaly detection achieves progress thanks to datasets such as MVTec-AD and VisA. However, they suffer from limitations in terms of the number of defect samples, types o…
cs.CV2022★ 5 cited
Self-Supervised Guided Segmentation Framework for Unsupervised Anomaly Detection
Peng Xing, Yanpeng Sun, Zechao Li
Unsupervised anomaly detection is a challenging task in industrial applications since it is impracticable to collect sufficient anomalous samples. In this paper, a novel Self-Super…