3 papers
cs.CV2026
Physics-inspired Pseudo Anomaly Generation and Prototype Feature Guidance for 3D Anomaly Detection
Jian Ning, Qin Zou, Linchun Wu +4
3D point cloud anomaly detection plays a vital role in industrial manufacturing, yet it faces significant challenges due to the scarcity and high acquisition cost of real anomalous…
cs.CV2026
Point Cloud Diffusion with Global and Local Reconstruction for Instance-Level 3D Anomaly Detection
Linchun Wu, Qin Zou, Jiwen Lu +1
3D anomaly detection in point clouds is critical for high-precision industrial manufacturing. Reconstruction-based methods have laid a strong foundation by detecting 3D anomalies t…
cs.CV2025
Double Helix Diffusion for Cross-Domain Anomaly Image Generation
Linchun Wu, Qin Zou, Xianbiao Qi +3
Visual anomaly inspection is critical in manufacturing, yet hampered by the scarcity of real anomaly samples for training robust detectors. Synthetic data generation presents a via…