OSD-IRF performs unsupervised industrial anomaly detection with a single diffusion step by evaluating anomalies in inverse residual field space under a Gaussian, delivering SOTA or competitive results with roughly 2x speedup.
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Flow Mismatching detects anomalies via aggregated velocity mismatches along noise-to-image paths in a flow matching model trained only on normal data, yielding pixel heatmaps without reconstruction or test-time optimization.
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One-Step Diffusion with Inverse Residual Fields for Unsupervised Industrial Anomaly Detection
OSD-IRF performs unsupervised industrial anomaly detection with a single diffusion step by evaluating anomalies in inverse residual field space under a Gaussian, delivering SOTA or competitive results with roughly 2x speedup.
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Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models
Flow Mismatching detects anomalies via aggregated velocity mismatches along noise-to-image paths in a flow matching model trained only on normal data, yielding pixel heatmaps without reconstruction or test-time optimization.