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 3831–3840 of 4856 papers

Title	Date	Tasks	Status
Multivariate Time Series Anomaly Detection via Dynamic Graph Forecasting	Feb 4, 2023	Anomaly DetectionTime Series	—Unverified
Contaminated Multivariate Time-Series Anomaly Detection with Spatio-Temporal Graph Conditional Diffusion Models	Aug 24, 2023	Anomaly DetectionTime Series	—Unverified
Multivariate Time Series Anomaly Detection in Industry 5.0	Mar 20, 2025	Anomaly DetectionTime Series	—Unverified
Multi-view Anomaly Detection via Probabilistic Latent Variable Models	Nov 13, 2014	Anomaly DetectionBayesian Inference	—Unverified
Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models	Dec 1, 2016	Anomaly DetectionBayesian Inference	—Unverified
Multi-view Contrastive Self-Supervised Learning of Accounting Data Representations for Downstream Audit Tasks	Sep 23, 2021	Anomaly DetectionAttribute	—Unverified
MultiView Diffusion Maps	Aug 23, 2015	Anomaly DetectionClustering	—Unverified
Multi-View Industrial Anomaly Detection with Epipolar Constrained Cross-View Fusion	Mar 14, 2025	Anomaly Detection	—Unverified
Naive Few-Shot Learning: Uncovering the fluid intelligence of machines	May 24, 2022	Anomaly DetectionFew-Shot Learning	—Unverified
Narrative based Postdictive Reasoning for Cognitive Robotics	Jun 4, 2013	Anomaly DetectionTranslation	—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