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 1251–1260 of 4856 papers

Title	Date	Tasks	Status	Hype
Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data	Apr 23, 2024	Anomaly DetectionFederated Learning	—Unverified	0
IPAD: Industrial Process Anomaly Detection Dataset	Apr 23, 2024	Anomaly DetectionVideo Anomaly Detection	—Unverified	0
A Neuro-Symbolic Explainer for Rare Events: A Case Study on Predictive Maintenance	Apr 21, 2024	Anomaly Detection	—Unverified	0
Detecting Compromised IoT Devices Using Autoencoders with Sequential Hypothesis Testing	Apr 21, 2024	Anomaly Detection	—Unverified	0
FiLo: Zero-Shot Anomaly Detection by Fine-Grained Description and High-Quality Localization	Apr 21, 2024	Anomaly DetectionPosition	CodeCode Available	2
Multi-feature Reconstruction Network using Crossed-mask Restoration for Unsupervised Industrial Anomaly Detection	Apr 20, 2024	Anomaly DetectionImage Reconstruction	—Unverified	0
Hyperspectral Anomaly Detection with Self-Supervised Anomaly Prior	Apr 20, 2024	Anomaly DetectionSelf-Supervised Learning	—Unverified	0
uTRAND: Unsupervised Anomaly Detection in Traffic Trajectories	Apr 19, 2024	Anomaly DetectionTrajectory Prediction	—Unverified	0
Detecting Out-Of-Distribution Earth Observation Images with Diffusion Models	Apr 19, 2024	Anomaly DetectionEarth Observation	—Unverified	0
Warped Time Series Anomaly Detection	Apr 18, 2024	Anomaly DetectionDynamic Time Warping	—Unverified	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