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 1971–1980 of 4856 papers

Title	Date	Tasks	Status	Hype
Graph-level Anomaly Detection via Hierarchical Memory Networks	Jul 3, 2023	Anomaly Detection	CodeCode Available	1
Graph Neural Networks based Log Anomaly Detection and Explanation	Jul 2, 2023	Anomaly DetectionGraph Neural Network	CodeCode Available	1
Morse Neural Networks for Uncertainty Quantification	Jul 2, 2023	Anomaly DetectionOne-class classifier	—Unverified	0
A MIL Approach for Anomaly Detection in Surveillance Videos from Multiple Camera Views	Jul 2, 2023	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	0
Hiding in Plain Sight: Differential Privacy Noise Exploitation for Evasion-resilient Localized Poisoning Attacks in Multiagent Reinforcement Learning	Jul 1, 2023	Anomaly Detection	—Unverified	0
Applied Bayesian Structural Health Monitoring: inclinometer data anomaly detection and forecasting	Jul 1, 2023	Anomaly DetectionDecision Making	—Unverified	0
A Comparative Study of Machine Learning Algorithms for Anomaly Detection in Industrial Environments: Performance and Environmental Impact	Jul 1, 2023	Anomaly Detection	—Unverified	0
Interpretable Anomaly Detection in Cellular Networks by Learning Concepts in Variational Autoencoders	Jun 28, 2023	Anomaly DetectionRepresentation Learning	—Unverified	0
Exploring Dual Model Knowledge Distillation for Anomaly Detection	Jun 27, 2023	Anomaly Detectionfeature selection	—Unverified	0
Learning normal asymmetry representations for homologous brain structures	Jun 27, 2023	Anomaly DetectionRepresentation Learning	CodeCode Available	0

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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