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 3181–3190 of 4856 papers

Title	Date	Tasks	Status
Statistical validation of a deep learning algorithm for dental anomaly detection in intraoral radiographs using paired data	Feb 1, 2024	Anomaly DetectionDeep Learning	—Unverified
Statistics and Deep Learning-based Hybrid Model for Interpretable Anomaly Detection	Feb 25, 2022	Anomaly DetectionDeep Learning	—Unverified
Steam Turbine Anomaly Detection: An Unsupervised Learning Approach Using Enhanced Long Short-Term Memory Variational Autoencoder	Nov 16, 2024	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
STemGAN: spatio-temporal generative adversarial network for video anomaly detection	Sep 22, 2023	Anomaly DetectionAnomaly Detection In Surveillance Videos	—Unverified
STGlow: A Flow-based Generative Framework with Dual Graphormer for Pedestrian Trajectory Prediction	Nov 21, 2022	Anomaly DetectionAutonomous Driving	—Unverified
STNMamba: Mamba-based Spatial-Temporal Normality Learning for Video Anomaly Detection	Dec 28, 2024	Anomaly DetectionMamba	—Unverified
Stochastic Earned Value Analysis using Monte Carlo Simulation and Statistical Learning Techniques	May 31, 2024	Anomaly Detection	—Unverified
Stochastic Functional Analysis and Multilevel Vector Field Anomaly Detection	Jul 11, 2022	Anomaly Detection	—Unverified
Stochastic tensor space feature theory with applications to robust machine learning	Oct 4, 2021	Anomaly DetectionBIG-bench Machine Learning	—Unverified
Stochastic Proximal AUC Maximization	Jun 14, 2019	Anomaly Detectionimbalanced classification	—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