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 3791–3800 of 4856 papers

Title	Date	Tasks	Status
Multi-Level Anomaly Detection on Time-Varying Graph Data	Oct 16, 2014	Anomaly DetectionGraph Anomaly Detection	—Unverified
Multi-level conformal clustering: A distribution-free technique for clustering and anomaly detection	Oct 17, 2019	Anomaly DetectionClustering	—Unverified
Multi-level hypothesis testing for populations of heterogeneous networks	Sep 7, 2018	Anomaly DetectionTwo-sample testing	—Unverified
Multi-level Memory-augmented Appearance-Motion Correspondence Framework for Video Anomaly Detection	Mar 9, 2023	Anomaly DetectionVideo Anomaly Detection	—Unverified
Multilevel Saliency-Guided Self-Supervised Learning for Image Anomaly Detection	Nov 30, 2023	Anomaly DetectionSelf-Supervised Learning	—Unverified
Multimedia Datasets for Anomaly Detection: A Review	Dec 10, 2021	Anomaly Detectionobject-detection	—Unverified
Multimodal Anomaly Detection based on Deep Auto-Encoder for Object Slip Perception of Mobile Manipulation Robots	Mar 6, 2024	Anomaly DetectionObject	—Unverified
Multimodal Attention-Enhanced Feature Fusion-based Weekly Supervised Anomaly Violence Detection	Sep 17, 2024	Anomaly DetectionOptical Flow Estimation	—Unverified
Multimodal RAG-driven Anomaly Detection and Classification in Laser Powder Bed Fusion using Large Language Models	May 20, 2025	Anomaly DetectionDescriptive	—Unverified
Multimodal Task Representation Memory Bank vs. Catastrophic Forgetting in Anomaly Detection	Feb 10, 2025	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	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