Research map / Label-efficient and robust learning / OOD and anomaly detection
Multi-View Anomaly Detection: Neighborhood in Locality Matters
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| estimate normal set with nearest-neighbor criterion (MUVAD-QPR) instead of cluster-based profiling | multi-view anomaly detector · Synthetic no-cluster data | AUC: 0.806 -> 1.000 | Helped |
| MUVAD-QPR vs strongest baselines on benchmark datasets | multi-view anomaly detector · UCI and News benchmarks (15 settings) | AUC: W/T/L 14/1/0 vs OCSVM, 12/3/0 vs CRMOD | Helped |
| MUVAD vs DMOD on CASME micro-expression detection | multi-view anomaly detector · CASME mean | AUC: 0.766 -> 0.818 | Helped |
| MUVAD vs DMOD on dissension-heavy NewsM | multi-view anomaly detector · NewsM 8% dissension 2% unanimous | AUC: 0.569 -> 0.596 | Mixed |
Closest papers by meaning
- UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection (CVPR 2025 · similarity 0.88)
- Unveiling Multi-View Anomaly Detection: Intra-view Decoupling and Inter-view Fusion (AAAI 2025 · similarity 0.88)
- Odd-One-Out: Anomaly Detection by Comparing with Neighbors (CVPR 2025 · similarity 0.87)
- One-to-Normal: Anomaly Personalization for Few-shot Anomaly Detection (NeurIPS 2024 · similarity 0.87)
- Advancing Video Anomaly Detection: A Concise Review and a New Dataset (NeurIPS 2024 · similarity 0.86)
- Towards a Unified Framework of Clustering-based Anomaly Detection (ICML 2025 · similarity 0.85)
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