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 2721–2730 of 4856 papers

Title	Date	Tasks	Status	Hype
ADBench: Anomaly Detection Benchmark	Jun 19, 2022	Anomaly DetectionOutlier Detection	CodeCode Available	3
3D unsupervised anomaly detection and localization through virtual multi-view projection and reconstruction: Clinical validation on low-dose chest computed tomography	Jun 18, 2022	Anomaly DetectionComputed Tomography (CT)	CodeCode Available	0
Multi-Contextual Predictions with Vision Transformer for Video Anomaly Detection	Jun 17, 2022	Anomaly DetectionVideo Anomaly Detection	—Unverified	0
Applications of Machine Learning to the Identification of Anomalous ER Claims	Jun 16, 2022	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
ARES: Locally Adaptive Reconstruction-based Anomaly Scoring	Jun 15, 2022	Anomaly DetectionDimensionality Reduction	CodeCode Available	0
Deep Isolation Forest for Anomaly Detection	Jun 14, 2022	Anomaly DetectionTime Series	CodeCode Available	1
Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets	Jun 13, 2022	Anomaly DetectionTime Series	—Unverified	0
Hierarchical Conditional Variational Autoencoder Based Acoustic Anomaly Detection	Jun 11, 2022	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified	0
Fast Deep Autoencoder for Federated learning	Jun 10, 2022	Anomaly DetectionEdge-computing	—Unverified	0
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data Stream	Jun 9, 2022	Anomaly Detection	CodeCode Available	1

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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	UniNet	Detection AUROC	99.9	—	Unverified
5	GLASS	Detection AUROC	99.9	—	Unverified
6	PBAS	Detection AUROC	99.8	—	Unverified
7	HETMM	Detection AUROC	99.8	—	Unverified
8	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	EfficientAD (early stopping)	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	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	DDAD	Detection AUROC	98.9	—	Unverified
7	GLASS	Detection AUROC	98.8	—	Unverified
8	DiffusionAD	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