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 1471–1480 of 4856 papers

Title	Date	Tasks	Status
Automatic Prompt Generation and Grounding Object Detection for Zero-Shot Image Anomaly Detection	Nov 28, 2024	Anomaly DetectionImage-text matching	—Unverified
A Machine Learning-based Anomaly Detection Framework in Life Insurance Contracts	Nov 26, 2024	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
GraphSubDetector: Time Series Subsequence Anomaly Detection via Density-Aware Adaptive Graph Neural Network	Nov 26, 2024	Anomaly DetectionGraph Neural Network	—Unverified
Rock the KASBA: Blazingly Fast and Accurate Time Series Clustering	Nov 26, 2024	Anomaly DetectionClustering	—Unverified
Anomaly Detection and Radio-frequency Interference Classification with Unsupervised Learning in Narrowband Radio Technosignature Searches	Nov 25, 2024	Anomaly DetectionClustering	—Unverified
ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift	Nov 25, 2024	Anomaly DetectionMulti-class Anomaly Detection	—Unverified
Revisiting DDIM Inversion for Controlling Defect Generation by Disentangling the Background	Nov 25, 2024	Anomaly DetectionDenoising	—Unverified
Graph Adapter of EEG Foundation Models for Parameter Efficient Fine Tuning	Nov 25, 2024	Anomaly DetectionEEG	—Unverified
Unsupervised Event Outlier Detection in Continuous Time	Nov 25, 2024	Anomaly DetectionData Augmentation	—Unverified
Anomaly Detection in California Electricity Price Forecasting: Enhancing Accuracy and Reliability Using Principal Component Analysis	Nov 25, 2024	Anomaly DetectionManagement	—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