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 541–550 of 4856 papers

Title	Date	Tasks	Status	Hype
Beyond Single-Modal Boundary: Cross-Modal Anomaly Detection through Visual Prototype and Harmonization	Jan 1, 2025	Anomaly Detection	CodeCode Available	0
Track Any Anomalous Object:A Granular Video Anomaly Detection Pipeline	Jan 1, 2025	Anomaly DetectionAnomaly Localization	—Unverified	0
OralXrays-9: Towards Hospital-Scale Panoramic X-ray Anomaly Detection via Personalized Multi-Object Query-Aware Mining	Jan 1, 2025	Anomaly DetectionDiagnostic	—Unverified	0
CNC: Cross-modal Normality Constraint for Unsupervised Multi-class Anomaly Detection	Dec 31, 2024	Anomaly DetectionAttribute	—Unverified	0
An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework	Dec 30, 2024	Anomaly DetectionModel Selection	—Unverified	0
Machine Learning-Based Security Policy Analysis	Dec 30, 2024	Anomaly Detection	—Unverified	0
SoftPatch+: Fully Unsupervised Anomaly Classification and Segmentation	Dec 30, 2024	Anomaly ClassificationAnomaly Detection	CodeCode Available	2
Cross-Modal Fusion and Attention Mechanism for Weakly Supervised Video Anomaly Detection	Dec 29, 2024	Anomaly DetectionGraph Attention	—Unverified	0
Exploring the Magnitude-Shape Plot Framework for Anomaly Detection in Crowded Video Scenes	Dec 29, 2024	Anomaly DetectionVideo Anomaly Detection	—Unverified	0
Dive into Time-Series Anomaly Detection: A Decade Review	Dec 29, 2024	Anomaly DetectionTime Series	CodeCode Available	0

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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	HETMM	Detection AUROC	99.8	—	Unverified
7	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	PBAS	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	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	DDAD	Detection AUROC	98.9	—	Unverified
6	Dinomaly ViT-L (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