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 3181–3190 of 4856 papers

Title	Date	Tasks	Status	Hype
A Distance-based Anomaly Detection Framework for Deep Reinforcement Learning	Sep 21, 2021	Anomaly DetectionAtari Games	—Unverified	0
Self-supervised Representation Learning for Reliable Robotic Monitoring of Fruit Anomalies	Sep 21, 2021	Anomaly DetectionData Augmentation	CodeCode Available	0
DeepTimeAnomalyViz: A Tool for Visualizing and Post-processing Deep Learning Anomaly Detection Results for Industrial Time-Series	Sep 21, 2021	Anomaly DetectionTime Series	—Unverified	0
A2Log: Attentive Augmented Log Anomaly Detection	Sep 20, 2021	Anomaly DetectionData Augmentation	—Unverified	0
Merlion: A Machine Learning Library for Time Series	Sep 20, 2021	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available	1
Anomaly Detection in Radar Data Using PointNets	Sep 20, 2021	Anomaly DetectionAutonomous Driving	—Unverified	0
Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection	Sep 20, 2021	Anomaly DetectionLesion Detection	CodeCode Available	0
Deep Spatio-temporal Sparse Decomposition for Trend Prediction and Anomaly Detection in Cardiac Electrical Conduction	Sep 20, 2021	Anomaly Detection	—Unverified	0
A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition	Sep 18, 2021	Anomaly DetectionTime Series	—Unverified	0
3-Dimensional Deep Learning with Spatial Erasing for Unsupervised Anomaly Segmentation in Brain MRI	Sep 14, 2021	Anomaly DetectionAnomaly Segmentation	—Unverified	0

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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