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 2361–2370 of 4856 papers

Title	Date	Tasks	Status
Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection	Apr 25, 2024	Anomaly DetectionGraph Anomaly Detection	—Unverified
Guarding the Grid: Enhancing Resilience in Automated Residential Demand Response Against False Data Injection Attacks	Dec 14, 2023	Anomaly DetectionDecision Making	—Unverified
Graph neural network-based lithium-ion battery state of health estimation using partial discharging curve	Aug 30, 2024	Anomaly DetectionGraph Neural Network	—Unverified
Graph Mixture of Experts and Memory-augmented Routers for Multivariate Time Series Anomaly Detection	Dec 26, 2024	Anomaly DetectionMixture-of-Experts	—Unverified
Client-Specific Anomaly Detection for Face Presentation Attack Detection	Jul 2, 2018	Anomaly DetectionDecision Making	—Unverified
Accurate and fast anomaly detection in industrial processes and IoT environments	Apr 27, 2024	Anomaly DetectionFeature Importance	—Unverified
Anomaly Detection in Trajectory Data with Normalizing Flows	Apr 13, 2020	Anomaly DetectionDensity Estimation	—Unverified
Hankel-structured Tensor Robust PCA for Multivariate Traffic Time Series Anomaly Detection	Oct 8, 2021	Anomaly DetectionTime Series	—Unverified
CLIP-AD: A Language-Guided Staged Dual-Path Model for Zero-shot Anomaly Detection	Nov 1, 2023	Anomaly DetectionLanguage Modeling	—Unverified
Anomaly Detection in Traffic Scenes via Spatial-aware Motion Reconstruction	Apr 30, 2019	Anomaly DetectionAutonomous Vehicles	—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