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 2781–2790 of 4856 papers

Title	Date	Tasks	Status
Conformalized Kernel Ridge Regression	Sep 19, 2016	Anomaly Detectionregression	—Unverified
Conformal k-NN Anomaly Detector for Univariate Data Streams	Jun 11, 2017	Anomaly DetectionConformal Prediction	—Unverified
Connecting Web Event Forecasting with Anomaly Detection: A Case Study on Enterprise Web Applications Using Self-Supervised Neural Networks	Aug 31, 2020	Anomaly DetectionSelf-Supervised Learning	—Unverified
Consensus Synergizes with Memory: A Simple Approach for Anomaly Segmentation in Urban Scenes	Nov 24, 2021	Anomaly DetectionAnomaly Segmentation	—Unverified
Constant Time EXPected Similarity Estimation using Stochastic Optimization	Nov 17, 2015	Anomaly DetectionStochastic Optimization	—Unverified
Constraining Anomaly Detection with Anomaly-Free Regions	Sep 30, 2024	Anomaly Detection	—Unverified
Constraint Guided AutoEncoders for Joint Optimization of Condition Indicator Estimation and Anomaly Detection in Machine Condition Monitoring	Sep 18, 2024	Anomaly DetectionDiagnostic	—Unverified
Constricting Normal Latent Space for Anomaly Detection with Normal-only Training Data	Mar 24, 2024	Anomaly DetectionVideo Anomaly Detection	—Unverified
Constructing a meta-learner for unsupervised anomaly detection	Apr 22, 2023	Anomaly DetectionAutoML	—Unverified
CONSULT: Contrastive Self-Supervised Learning for Few-shot Tumor Detection	Oct 15, 2024	Anomaly DetectionContrastive Learning	—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	GLASS	Detection AUROC	99.9	—	Unverified
5	UniNet	Detection AUROC	99.9	—	Unverified
6	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
7	DDAD	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	PBAS	Detection AUROC	99.8	—	Unverified
10	HETMM	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	DDAD	Detection AUROC	98.9	—	Unverified
5	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	INP-Former ViT-B (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