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 2391–2400 of 4856 papers

Title	Date	Tasks	Status
HFN: Heterogeneous Feature Network for Multivariate Time Series Anomaly Detection	Nov 1, 2022	Anomaly DetectionGraph structure learning	—Unverified
Hiding in Plain Sight: Differential Privacy Noise Exploitation for Evasion-resilient Localized Poisoning Attacks in Multiagent Reinforcement Learning	Jul 1, 2023	Anomaly Detection	—Unverified
Hierarchical Conditional Variational Autoencoder Based Acoustic Anomaly Detection	Jun 11, 2022	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
Hierarchical Deep Learning with Generative Adversarial Network for Automatic Cardiac Diagnosis from ECG Signals	Oct 19, 2022	Anomaly DetectionGenerative Adversarial Network	—Unverified
GraphDART: Graph Distillation for Efficient Advanced Persistent Threat Detection	Jan 6, 2025	Anomaly DetectionComputational Efficiency	—Unverified
Hierarchical Semantic Contrast for Scene-aware Video Anomaly Detection	Mar 23, 2023	Anomaly DetectionContrastive Learning	—Unverified
Clustering of Time Series Data with Prior Geographical Information	Jul 3, 2021	Anomaly DetectionClustering	—Unverified
Imbalanced Aircraft Data Anomaly Detection	May 17, 2023	Anomaly DetectionTime Series	—Unverified
Anomaly Detection in Time Series of EDFA Pump Currents to Monitor Degeneration Processes using Fuzzy Clustering	Aug 12, 2024	Anomaly DetectionChange Detection	—Unverified
Graph Coding for Model Selection and Anomaly Detection in Gaussian Graphical Models	Feb 4, 2021	Anomaly DetectionModel Selection	—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