RADAR produces anomaly maps directly from attention-based diffusion models in a single forward pass, achieving higher F1 scores than reconstruction-based diffusion and statistical baselines on MVTec-AD and 3D-printed material data.
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SMAC detects shape deformations and color anomalies in 4D point clouds using Laplace-Beltrami spectral properties without registration or mesh reconstruction.
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Single-Step Reconstruction-Free Anomaly Detection and Segmentation via Diffusion Models
RADAR produces anomaly maps directly from attention-based diffusion models in a single forward pass, achieving higher F1 scores than reconstruction-based diffusion and statistical baselines on MVTec-AD and 3D-printed material data.
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Simultaneous Monitoring of Shape and Surface Color via 4D Point Clouds: A Registration-free Approach
SMAC detects shape deformations and color anomalies in 4D point clouds using Laplace-Beltrami spectral properties without registration or mesh reconstruction.