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 2141–2150 of 4856 papers

Title	Date	Tasks	Status	Hype
PAC-Based Formal Verification for Out-of-Distribution Data Detection	Apr 4, 2023	Anomaly DetectionAutonomous Vehicles	—Unverified	0
OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And Forecasting	Apr 4, 2023	Anomaly DetectionTime Series	CodeCode Available	1
DynamoPMU: A Physics Informed Anomaly Detection and Prediction Methodology using non-linear dynamics from μPMU Measurement Data	Mar 31, 2023	Anomaly DetectionEvent Detection	—Unverified	0
You Only Train Once: Learning a General Anomaly Enhancement Network with Random Masks for Hyperspectral Anomaly Detection	Mar 31, 2023	Anomaly DetectionModel Selection	CodeCode Available	1
Unsupervised crack detection on complex stone masonry surfaces	Mar 31, 2023	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	0
Time-series Anomaly Detection based on Difference Subspace between Signal Subspaces	Mar 31, 2023	Anomaly DetectionTime Series	—Unverified	0
Unsupervised Anomaly Detection and Localization of Machine Audio: A GAN-based Approach	Mar 31, 2023	Anomaly DetectionAnomaly Localization	CodeCode Available	1
Long-Short Temporal Co-Teaching for Weakly Supervised Video Anomaly Detection	Mar 31, 2023	Anomaly DetectionMultiple Instance Learning	CodeCode Available	1
Visual Anomaly Detection via Dual-Attention Transformer and Discriminative Flow	Mar 31, 2023	Anomaly Detection	CodeCode Available	1
ISSTAD: Incremental Self-Supervised Learning Based on Transformer for Anomaly Detection and Localization	Mar 30, 2023	Anomaly DetectionAnomaly Localization	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