Anomaly Detection

Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.

[Image source]: GAN-based Anomaly Detection in Imbalance Problems

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 3381–3390 of 4856 papers

Title	Date	Tasks	Status
TrustMAE: A Noise-Resilient Defect Classification Framework using Memory-Augmented Auto-Encoders with Trust Regions	Dec 29, 2020	Anomaly DetectionPerceptual Distance	—Unverified
Trustworthy Anomaly Detection: A Survey	Feb 15, 2022	Anomaly DetectionFairness	—Unverified
Trustworthy Intrusion Detection: Confidence Estimation Using Latent Space	Sep 19, 2024	Anomaly DetectionBinary Classification	—Unverified
Try with Simpler -- An Evaluation of Improved Principal Component Analysis in Log-based Anomaly Detection	Aug 24, 2023	Anomaly Detection	—Unverified
TS3IM: Unveiling Structural Similarity in Time Series through Image Similarity Assessment Insights	May 10, 2024	Anomaly DetectionDynamic Time Warping	—Unverified
TSPulse: Dual Space Tiny Pre-Trained Models for Rapid Time-Series Analysis	May 19, 2025	Anomaly DetectionDisentanglement	—Unverified
TTA-OOD: Test-time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision	Jul 19, 2024	Anomaly DetectionOut-of-Distribution Detection	—Unverified
Two methods for Jamming Identification in UAVs Networks using New Synthetic Dataset	Mar 21, 2022	Anomaly DetectionTime Series	—Unverified
Two-phase Dual COPOD Method for Anomaly Detection in Industrial Control System	Apr 30, 2023	Anomaly DetectionOutlier Detection	—Unverified
Two-Stage Deep Anomaly Detection with Heterogeneous Time Series Data	Feb 10, 2022	Anomaly DetectionTime Series	—Unverified

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All datasets MVTec AD VisA MVTec LOCO AD One-class CIFAR-10 CUHK Avenue ShanghaiTech Fishyscapes L&F UCR Anomaly Archive MPDD BTAD One-class CIFAR-100 UBnormal

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	CPR-faster(TensorRT)	FPS	1,016	—	Unverified
2	CPR-fast(TensorRT)	FPS	362	—	Unverified
3	CPR(TensorRT)	FPS	130	—	Unverified
4	UniNet	Detection AUROC	99.9	—	Unverified
5	GLASS	Detection AUROC	99.9	—	Unverified
6	PBAS	Detection AUROC	99.8	—	Unverified
7	HETMM	Detection AUROC	99.8	—	Unverified
8	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UniNet	Detection AUROC	99.8	—	Unverified
2	GLAD	Detection AUROC	99.5	—	Unverified
3	UniNet(model-unified multi-class)	Detection AUROC	99.15	—	Unverified
4	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	DDAD	Detection AUROC	98.9	—	Unverified
7	GLASS	Detection AUROC	98.8	—	Unverified
8	DiffusionAD	Detection AUROC	98.8	—	Unverified
9	TransFusion	Detection AUROC	98.7	—	Unverified
10	HETMM	Detection AUROC	98.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CSAD	Avg. Detection AUROC	95.3	—	Unverified
2	PSAD	Avg. Detection AUROC	94.9	—	Unverified