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 3221–3230 of 4856 papers

Title	Date	Tasks	Status
Synthetic Aperture Anomaly Imaging	Apr 26, 2023	Anomaly Detection	—Unverified
Synthetic outlier generation for anomaly detection in autonomous driving	Aug 4, 2023	Anomaly DetectionAutonomous Driving	—Unverified
Synthetic Pseudo Anomalies for Unsupervised Video Anomaly Detection: A Simple yet Efficient Framework based on Masked Autoencoder	Mar 9, 2023	Anomaly DetectionOne-Class Classification	—Unverified
Synthetic User Behavior Sequence Generation with Large Language Models for Smart Homes	Jan 31, 2025	Anomaly DetectionDataset Generation	—Unverified
Systematic Review: Anomaly Detection in Connected and Autonomous Vehicles	May 4, 2024	Anomaly DetectionArticles	—Unverified
System Calls for Malware Detection and Classification: Methodologies and Applications	Jun 2, 2025	Anomaly DetectionMalware Analysis	—Unverified
TAAD: Time-varying adversarial anomaly detection in dynamic graphs	Oct 14, 2024	Anomaly Detection	—Unverified
TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models	Jul 23, 2023	Anomaly DetectionDensity Estimation	—Unverified
TAB: Text-Align Anomaly Backbone Model for Industrial Inspection Tasks	Dec 15, 2023	Anomaly ClassificationAnomaly Detection	—Unverified
Tackling Diverse Minorities in Imbalanced Classification	Aug 28, 2023	Anomaly DetectionClassification	—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