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 2261–2270 of 4856 papers

Title	Date	Tasks	Status
KnowSafe: Combined Knowledge and Data Driven Hazard Mitigation in Artificial Pancreas Systems	Nov 13, 2023	Anomaly Detection	—Unverified
Open-Set Graph Anomaly Detection via Normal Structure Regularisation	Nov 12, 2023	Anomaly DetectionGraph Anomaly Detection	—Unverified
Dual-Branch Reconstruction Network for Industrial Anomaly Detection with RGB-D Data	Nov 12, 2023	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
DeepQC: A Deep Learning System for Automatic Quality Control of In-situ Soil Moisture Sensor Time Series Data	Nov 12, 2023	Anomaly DetectionTime Series	—Unverified
CL-Flow:Strengthening the Normalizing Flows by Contrastive Learning for Better Anomaly Detection	Nov 12, 2023	Anomaly DetectionContrastive Learning	—Unverified
VT-Former: An Exploratory Study on Vehicle Trajectory Prediction for Highway Surveillance through Graph Isomorphism and Transformer	Nov 11, 2023	Anomaly DetectionAutonomous Driving	—Unverified
GRAM: An Interpretable Approach for Graph Anomaly Detection using Gradient Attention Maps	Nov 10, 2023	Anomaly DetectionDecision Making	—Unverified
k-Parameter Approach for False In-Season Anomaly Suppression in Daily Time Series Anomaly Detection	Nov 10, 2023	Anomaly DetectionPosition	—Unverified
Ball Mill Fault Prediction Based on Deep Convolutional Auto-Encoding Network	Nov 9, 2023	Anomaly DetectionFault Detection	—Unverified
Explained anomaly detection in text reviews: Can subjective scenarios be correctly evaluated?	Nov 8, 2023	Anomaly Detection	—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