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 3981–3990 of 4856 papers

Title	Date	Tasks	Status	Hype
A Characteristic Function for Shapley-Value-Based Attribution of Anomaly Scores	Apr 9, 2020	Anomaly DetectionSemi-supervised Anomaly Detection	CodeCode Available	0
Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers	Apr 8, 2020	Anomaly ClassificationAnomaly Detection	—Unverified	0
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study	Apr 7, 2020	AnatomyAnomaly Detection	CodeCode Available	1
pAElla: Edge-AI based Real-Time Malware Detection in Data Centers	Apr 7, 2020	Anomaly DetectionEdge-computing	CodeCode Available	0
Challenges in Vessel Behavior and Anomaly Detection: From Classical Machine Learning to Deep Learning	Apr 7, 2020	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
When, Where, and What? A New Dataset for Anomaly Detection in Driving Videos	Apr 6, 2020	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	1
Moving Metric Detection and Alerting System at eBay	Apr 6, 2020	Anomaly DetectionRetrieval	—Unverified	0
ReRe: A Lightweight Real-time Ready-to-Go Anomaly Detection Approach for Time Series	Apr 5, 2020	Anomaly DetectionIntrusion Detection	—Unverified	0
Any-Shot Sequential Anomaly Detection in Surveillance Videos	Apr 5, 2020	Anomaly DetectionAnomaly Detection In Surveillance Videos	—Unverified	0
Anomaly Detection and Prototype Selection Using Polyhedron Curvature	Apr 5, 2020	Anomaly DetectionDenoising	CodeCode Available	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