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 2751–2760 of 4856 papers

Title	Date	Tasks	Status	Hype
Dual-stream spatiotemporal networks with feature sharing for monitoring animals in the home cage	Jun 1, 2022	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified	0
Proximally Sensitive Error for Anomaly Detection and Feature Learning	Jun 1, 2022	Anomaly Detection	—Unverified	0
Attack-Agnostic Adversarial Detection	Jun 1, 2022	Adversarial AttackAdversarial Attack Detection	—Unverified	0
MAD-EN: Microarchitectural Attack Detection through System-wide Energy Consumption	May 31, 2022	Anomaly DetectionDiversity	CodeCode Available	0
Rethinking Graph Neural Networks for Anomaly Detection	May 31, 2022	Anomaly DetectionGraph Anomaly Detection	CodeCode Available	2
Robust Projection based Anomaly Extraction (RPE) in Univariate Time-Series	May 31, 2022	Anomaly DetectionTime Series	—Unverified	0
Grid HTM: Hierarchical Temporal Memory for Anomaly Detection in Videos	May 30, 2022	Anomaly DetectionDeep Learning	CodeCode Available	0
Benchmarking Unsupervised Anomaly Detection and Localization	May 30, 2022	Anomaly DetectionBenchmarking	—Unverified	0
Unfooling Perturbation-Based Post Hoc Explainers	May 29, 2022	Adversarial AttackAnomaly Detection	CodeCode Available	0
Diminishing Empirical Risk Minimization for Unsupervised Anomaly Detection	May 29, 2022	Anomaly DetectionUnsupervised Anomaly Detection	—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	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