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 391–400 of 4856 papers

Title	Date	Tasks	Status	Hype
Adaptive Sparsified Graph Learning Framework for Vessel Behavior Anomalies	Feb 20, 2025	Anomaly DetectionGraph Learning	—Unverified	0
CyberSentinel: An Emergent Threat Detection System for AI Security	Feb 20, 2025	Anomaly Detection	—Unverified	0
dtaianomaly: A Python library for time series anomaly detection	Feb 20, 2025	Anomaly DetectionTime Series	CodeCode Available	2
Graph Anomaly Detection via Adaptive Test-time Representation Learning across Out-of-Distribution Domains	Feb 20, 2025	Anomaly DetectionGraph Anomaly Detection	—Unverified	0
A Synergy Scoring Filter for Unsupervised Anomaly Detection with Noisy Data	Feb 19, 2025	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified	0
Unlocking Multimodal Integration in EHRs: A Prompt Learning Framework for Language and Time Series Fusion	Feb 19, 2025	Anomaly DetectionPrompt Learning	—Unverified	0
Flow-based generative models as iterative algorithms in probability space	Feb 19, 2025	Anomaly DetectionDensity Estimation	—Unverified	0
Unsupervised Anomaly Detection through Mass Repulsing Optimal Transport	Feb 18, 2025	Anomaly DetectionFault Detection	CodeCode Available	0
Anomaly Detection in Smart Power Grids with Graph-Regularized MS-SVDD: a Multimodal Subspace Learning Approach	Feb 18, 2025	Anomaly DetectionEvent Detection	—Unverified	0
VUS: Effective and Efficient Accuracy Measures for Time-Series Anomaly Detection	Feb 18, 2025	Anomaly DetectionInformation Retrieval	CodeCode Available	2

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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