MMVIAD is the first multi-view continuous video dataset for industrial anomaly detection with four supported tasks, and the VISTA model improves average benchmark scores from 45.0 to 57.5 on unseen data while surpassing GPT-5.4.
Pad: A dataset and benchmark for pose-agnostic anomaly detection.Advances in Neural Information Processing Systems, 36:44558–44571
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ASBench is the first dedicated benchmark for anomaly synthesis algorithms, assessing them on generalization across datasets, synthetic-to-real data ratios, metric correlations, and hybrid strategies.
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MMVIAD: Multi-view Multi-task Video Understanding for Industrial Anomaly Detection
MMVIAD is the first multi-view continuous video dataset for industrial anomaly detection with four supported tasks, and the VISTA model improves average benchmark scores from 45.0 to 57.5 on unseen data while surpassing GPT-5.4.
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ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection
ASBench is the first dedicated benchmark for anomaly synthesis algorithms, assessing them on generalization across datasets, synthetic-to-real data ratios, metric correlations, and hybrid strategies.