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 1511–1520 of 4856 papers

Title	Date	Tasks	Status	Score
ALFA: A Dataset for UAV Fault and Anomaly Detection	Jul 14, 2019	Anomaly DetectionFault Detection	CodeCode Available	5
Explain First, Trust Later: LLM-Augmented Explanations for Graph-Based Crypto Anomaly Detection	Jun 17, 2025	Anomaly Detection	CodeCode Available	5
Explainable Anomaly Detection for Industrial Control System Cybersecurity	May 4, 2022	Anomaly DetectionExplainable artificial intelligence	CodeCode Available	5
Explainable Debugger for Black-box Machine Learning Models	Jul 18, 2021	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available	5
Expected Similarity Estimation for Large-Scale Batch and Streaming Anomaly Detection	Jan 25, 2016	Anomaly DetectionIncremental Learning	CodeCode Available	5
Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data	May 29, 2024	Anomaly DetectionSemi-supervised Anomaly Detection	CodeCode Available	5
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection	May 9, 2025	3D Anomaly Detection3D Anomaly Detection and Segmentation	CodeCode Available	5
Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation	Jun 12, 2020	Anomaly DetectionDensity Ratio Estimation	CodeCode Available	5
Enhancing Interpretability and Generalizability in Extended Isolation Forests	Oct 9, 2023	Anomaly DetectionFeature Importance	CodeCode Available	5
CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities	Oct 5, 2018	Anomaly DetectionClustering	CodeCode Available	5

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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