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 1981–1990 of 4856 papers

Title	Date	Tasks	Status
CARE to Compare: A real-world dataset for anomaly detection in wind turbine data	Apr 16, 2024	Anomaly DetectionFault Detection	—Unverified
Explainable Online Unsupervised Anomaly Detection for Cyber-Physical Systems via Causal Discovery from Time Series	Apr 15, 2024	Anomaly DetectionCausal Discovery	CodeCode Available
Polynomial Selection in Spectral Graph Neural Networks: An Error-Sum of Function Slices Approach	Apr 15, 2024	Anomaly DetectionGraph Anomaly Detection	CodeCode Available
Do LLMs Understand Visual Anomalies? Uncovering LLM's Capabilities in Zero-shot Anomaly Detection	Apr 15, 2024	Anomaly DetectionAnomaly Localization	—Unverified
Fault Detection in Mobile Networks Using Diffusion Models	Apr 14, 2024	Anomaly DetectionDiversity	—Unverified
Machine learning-based identification of Gaia astrometric exoplanet orbits	Apr 14, 2024	Anomaly DetectionFeature Importance	CodeCode Available
Reap the Wild Wind: Detecting Media Storms in Large-Scale News Corpora	Apr 14, 2024	Anomaly DetectionArticles	—Unverified
Label-free Anomaly Detection in Aerial Agricultural Images with Masked Image Modeling	Apr 13, 2024	Anomaly DetectionSelf-Supervised Learning	—Unverified
HCL-MTSAD: Hierarchical Contrastive Consistency Learning for Accurate Detection of Industrial Multivariate Time Series Anomalies	Apr 12, 2024	Anomaly DetectionContrastive Learning	—Unverified
Text Prompt with Normality Guidance for Weakly Supervised Video Anomaly Detection	Apr 12, 2024	Anomaly DetectionDomain Adaptation	—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	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