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 2661–2670 of 4856 papers

Title	Date	Tasks	Status	Hype
Unsupervised Industrial Anomaly Detection via Pattern Generative and Contrastive Networks	Jul 20, 2022	Anomaly DetectionAnomaly Localization	—Unverified	0
Anomaly Detection of Smart Metering System for Power Management with Battery Storage System/Electric Vehicle	Jul 20, 2022	Anomaly DetectionManagement	—Unverified	0
A Hybrid Convolutional Neural Network with Meta Feature Learning for Abnormality Detection in Wireless Capsule Endoscopy Images	Jul 20, 2022	Anomaly DetectionDiagnostic	—Unverified	0
Informative knowledge distillation for image anomaly segmentation	Jul 19, 2022	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1
RESAM: Requirements Elicitation and Specification for Deep-Learning Anomaly Models with Applications to UAV Flight Controllers	Jul 18, 2022	Anomaly DetectionDiagnostic	—Unverified	0
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications	Jul 18, 2022	Activity RecognitionAnomaly Detection	—Unverified	0
Self-Supervised-RCNN for Medical Image Segmentation with Limited Data Annotation	Jul 17, 2022	Anomaly DetectionImage Segmentation	—Unverified	0
Task-aware Similarity Learning for Event-triggered Time Series	Jul 17, 2022	Anomaly DetectionTime Series	—Unverified	0
SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection	Jul 16, 2022	Anomaly DetectionKnowledge Distillation	—Unverified	0
Greykite: Deploying Flexible Forecasting at Scale at LinkedIn	Jul 15, 2022	Anomaly DetectionTime Series	CodeCode Available	3

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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