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 501–510 of 4856 papers

Title	Date	Tasks	Status	Hype
Transformer-based Multivariate Time Series Anomaly Localization	Jan 15, 2025	Anomaly DetectionAnomaly Localization	—Unverified	0
Detecting Contextual Anomalies by Discovering Consistent Spatial Regions	Jan 14, 2025	Anomaly DetectionClustering	—Unverified	0
Multiple-Input Variational Auto-Encoder for Anomaly Detection in Heterogeneous Data	Jan 14, 2025	Anomaly Detection	—Unverified	0
STTS-EAD: Improving Spatio-Temporal Learning Based Time Series Prediction via	Jan 14, 2025	Anomaly DetectionMultivariate Time Series Forecasting	—Unverified	0
Unsupervised Feature Construction for Anomaly Detection in Time Series -- An Evaluation	Jan 14, 2025	Anomaly DetectionTime Series	—Unverified	0
ADKGD: Anomaly Detection in Knowledge Graphs with Dual-Channel Training	Jan 13, 2025	Anomaly DetectionKnowledge Graphs	CodeCode Available	0
Generative AI Enabled Robust Sensor Placement in Cyber-Physical Power Systems: A Graph Diffusion Approach	Jan 12, 2025	Anomaly DetectionDenoising	—Unverified	0
Driver Age and Its Effect on Key Driving Metrics: Insights from Dynamic Vehicle Data	Jan 12, 2025	Anomaly Detection	—Unverified	0
Active Rule Mining for Multivariate Anomaly Detection in Radio Access Networks	Jan 11, 2025	Anomaly DetectionTime Series	—Unverified	0
Exploring Pose-Based Anomaly Detection for Retail Security: A Real-World Shoplifting Dataset and Benchmark	Jan 11, 2025	Anomaly DetectionPose-based Anomaly Detection	CodeCode Available	1

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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	GLASS	Detection AUROC	99.9	—	Unverified
5	UniNet	Detection AUROC	99.9	—	Unverified
6	HETMM	Detection AUROC	99.8	—	Unverified
7	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	PBAS	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	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	DDAD	Detection AUROC	98.9	—	Unverified
6	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
7	DiffusionAD	Detection AUROC	98.8	—	Unverified
8	GLASS	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