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 1641–1650 of 4856 papers

Title	Date	Tasks	Status	Score
SAM-kNN Regressor for Online Learning in Water Distribution Networks	Apr 4, 2022	Anomaly Detection	CodeCode Available	5
Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features	Apr 13, 2018	Anomaly DetectionDecision Making	CodeCode Available	5
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health Episodes	Oct 22, 2020	Anomaly DetectionTime Series	CodeCode Available	5
Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory Tracing	Jun 9, 2021	Anomaly Detectionvehicle detection	CodeCode Available	5
Coupled-Space Attacks against Random-Walk-based Anomaly Detection	Jul 26, 2023	Anomaly DetectionGraph Anomaly Detection	CodeCode Available	5
AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal Properties	Oct 31, 2024	Anomaly Detectioncounterfactual	CodeCode Available	5
Braced Fourier Continuation and Regression for Anomaly Detection	May 6, 2024	Anomaly Detectionregression	CodeCode Available	5
Bounding Boxes and Probabilistic Graphical Models: Video Anomaly Detection Simplified	Jul 8, 2024	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	5
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning	Feb 8, 2025	Anomaly DetectionFederated Learning	CodeCode Available	5
Adaptive Anomaly Detection in Chaotic Time Series with a Spatially Aware Echo State Network	Sep 2, 2019	Anomaly DetectionTime Series	CodeCode Available	5

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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