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 1201–1210 of 4856 papers

Title	Date	Tasks	Status
Multi-View Industrial Anomaly Detection with Epipolar Constrained Cross-View Fusion	Mar 14, 2025	Anomaly Detection	—Unverified
Hoi2Anomaly: An Explainable Anomaly Detection Approach Guided by Human-Object Interaction	Mar 13, 2025	Anomaly DetectionHuman-Object Interaction Detection	—Unverified
G^2SF-MIAD: Geometry-Guided Score Fusion for Multimodal Industrial Anomaly Detection	Mar 13, 2025	Anomaly Detection	—Unverified
Time-EAPCR: A Deep Learning-Based Novel Approach for Anomaly Detection Applied to the Environmental Field	Mar 12, 2025	Anomaly Detection	—Unverified
A systematic literature review of unsupervised learning algorithms for anomalous traffic detection based on flows	Mar 11, 2025	Anomaly DetectionArticles	—Unverified
Probabilistic Segmentation for Robust Field of View Estimation	Mar 10, 2025	Anomaly DetectionAutonomous Vehicles	—Unverified
A Time Series Multitask Framework Integrating a Large Language Model, Pre-Trained Time Series Model, and Knowledge Graph	Mar 10, 2025	Anomaly DetectionDecoder	—Unverified
Self-supervised Normality Learning and Divergence Vector-guided Model Merging for Zero-shot Congenital Heart Disease Detection in Fetal Ultrasound Videos	Mar 10, 2025	Anomaly DetectionPrivacy Preserving	—Unverified
ECNN: A Low-complex, Adjustable CNN for Industrial Pump Monitoring Using Vibration Data	Mar 10, 2025	Anomaly Detection	—Unverified
Task-Oriented Connectivity for Networked Robotics with Generative AI and Semantic Communications	Mar 9, 2025	Anomaly DetectionSemantic Communication	—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