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 421–430 of 4856 papers

Title	Date	Tasks	Status	Hype
Advancing Precision Oncology Through Modeling of Longitudinal and Multimodal Data	Feb 11, 2025	Anomaly DetectionData Integration	—Unverified	0
Advancing climate model interpretability: Feature attribution for Arctic melt anomalies	Feb 11, 2025	Anomaly Detectioncounterfactual	—Unverified	0
FADE: Forecasting for Anomaly Detection on ECG	Feb 11, 2025	Anomaly DetectionDomain Adaptation	CodeCode Available	0
Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models	Feb 11, 2025	Anomaly Detectionzero-shot anomaly detection	—Unverified	0
Towards Copyright Protection for Knowledge Bases of Retrieval-augmented Language Models via Reasoning	Feb 10, 2025	Anomaly DetectionRAG	—Unverified	0
Multimodal Task Representation Memory Bank vs. Catastrophic Forgetting in Anomaly Detection	Feb 10, 2025	Anomaly DetectionContrastive Learning	—Unverified	0
Foundation Models for Anomaly Detection: Vision and Challenges	Feb 10, 2025	Anomaly Detection	—Unverified	0
SAFE: Self-Supervised Anomaly Detection Framework for Intrusion Detection	Feb 10, 2025	Anomaly DetectionIntrusion Detection	—Unverified	0
Leveraging GPT-4o Efficiency for Detecting Rework Anomaly in Business Processes	Feb 10, 2025	Anomaly Detection	—Unverified	0
3CAD: A Large-Scale Real-World 3C Product Dataset for Unsupervised Anomaly	Feb 9, 2025	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	2

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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