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 1001–1010 of 4856 papers

Title	Date	Tasks	Status	Hype
Synthetic Time Series for Anomaly Detection in Cloud Microservices	Jul 21, 2024	Anomaly DetectionCloud Computing	—Unverified	0
Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound	Jul 21, 2024	Anomaly DetectionDenoising	—Unverified	0
Decentralized Federated Anomaly Detection in Smart Grids: A P2P Gossip Approach	Jul 20, 2024	Anomaly DetectionFederated Learning	—Unverified	0
TTA-OOD: Test-time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision	Jul 19, 2024	Anomaly DetectionOut-of-Distribution Detection	—Unverified	0
Motif-Consistent Counterfactuals with Adversarial Refinement for Graph-Level Anomaly Detection	Jul 18, 2024	Anomaly Detectioncounterfactual	—Unverified	0
A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos	Jul 17, 2024	Anomaly DetectionAnomaly Detection In Surveillance Videos	—Unverified	0
In-Situ Infrared Camera Monitoring for Defect and Anomaly Detection in Laser Powder Bed Fusion: Calibration, Data Mapping, and Feature Extraction	Jul 17, 2024	3D geometryAnomaly Detection	—Unverified	0
GeneralAD: Anomaly Detection Across Domains by Attending to Distorted Features	Jul 17, 2024	Anomaly DetectionSelf-Driving Cars	CodeCode Available	2
Leveraging the Mahalanobis Distance to enhance Unsupervised Brain MRI Anomaly Detection	Jul 17, 2024	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	0
VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation	Jul 17, 2024	Anomaly DetectionAnomaly Segmentation	CodeCode Available	2

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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