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 3011–3020 of 4856 papers

Title	Date	Tasks	Status
Sampling - Variational Auto Encoder - Ensemble: In the Quest of Explainable Artificial Intelligence	Sep 25, 2023	Anomaly DetectionExplainable artificial intelligence	—Unverified
Satellite Anomaly Detection Using Variance Based Genetic Ensemble of Neural Networks	Feb 10, 2023	Anomaly Detection	—Unverified
SCADE: Scalable Framework for Anomaly Detection in High-Performance System	Dec 5, 2024	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
Log-based Anomaly Detection based on EVT Theory with feedback	Jun 8, 2023	Anomaly Detection	—Unverified
Scalable and Decentralized Algorithms for Anomaly Detection via Learning-Based Controlled Sensing	Dec 8, 2021	Anomaly DetectionDecision Making	—Unverified
Scalable Anomaly Detection in Large Homogenous Populations	Sep 20, 2013	Anomaly DetectionCombinatorial Optimization	—Unverified
Scalable Multi-Task Gaussian Process Tensor Regression for Normative Modeling of Structured Variation in Neuroimaging Data	Jul 31, 2018	Anomaly DetectionMulti-Task Learning	—Unverified
SCALA: Sparsification-based Contrastive Learning for Anomaly Detection on Attributed Networks	Jan 3, 2024	Anomaly DetectionContrastive Learning	—Unverified
Scaling New Peaks: A Viewership-centric Approach to Automated Content Curation	Aug 9, 2021	Anomaly Detection	—Unverified
SCANIA Component X Dataset: A Real-World Multivariate Time Series Dataset for Predictive Maintenance	Jan 26, 2024	Anomaly DetectionSurvival Analysis	—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