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 3881–3890 of 4856 papers

Title	Date	Tasks	Status
Normalizing flows for novelty detection in industrial time series data	Jun 17, 2019	Anomaly DetectionNovelty Detection	—Unverified
No Shifted Augmentations (NSA): compact distributions for robust self-supervised Anomaly Detection	Mar 19, 2022	Anomaly DetectionOut of Distribution (OOD) Detection	—Unverified
No Shifted Augmentations (NSA): strong baselines for self-supervised Anomaly Detection	Sep 29, 2021	Anomaly DetectionOut of Distribution (OOD) Detection	—Unverified
Novel Applications for VAE-based Anomaly Detection Systems	Apr 26, 2022	Anomaly Detection	—Unverified
Novel machine learning applications at the LHC	Sep 30, 2024	Anomaly Detection	—Unverified
Novel semi-metrics for multivariate change point analysis and anomaly detection	Nov 4, 2019	Anomaly DetectionTime Series	—Unverified
Novelty Detection for Election Fraud: A Case Study with Agent-Based Simulation Data	Nov 29, 2022	Anomaly DetectionNovelty Detection	—Unverified
N-pad : Neighboring Pixel-based Industrial Anomaly Detection	Oct 17, 2022	Anomaly DetectionAnomaly Segmentation	—Unverified
NUMOSIM: A Synthetic Mobility Dataset with Anomaly Detection Benchmarks	Sep 4, 2024	Anomaly DetectionBenchmarking	—Unverified
NVAE-GAN Based Approach for Unsupervised Time Series Anomaly Detection	Jan 8, 2021	Anomaly DetectionTime Series	—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