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 501–510 of 4856 papers

Title	Date	Tasks	Status	Hype
Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attention	Feb 14, 2023	Anomaly Detection	CodeCode Available	1
Deep Orthogonal Hypersphere Compression for Anomaly Detection	Feb 13, 2023	Anomaly Detection	CodeCode Available	1
Explainable Anomaly Detection in Images and Videos: A Survey	Feb 13, 2023	Anomaly DetectionSurvey	CodeCode Available	1
Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Models	Feb 10, 2023	Anomaly DetectionEvent Detection	CodeCode Available	1
Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection	Feb 10, 2023	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	1
Weakly Supervised Anomaly Detection: A Survey	Feb 9, 2023	Anomaly DetectionSupervised Anomaly Detection	CodeCode Available	1
Perception Datasets for Anomaly Detection in Autonomous Driving: A Survey	Feb 6, 2023	Anomaly DetectionAutonomous Driving	CodeCode Available	1
Window Size Selection in Unsupervised Time Series Analytics: A Review and Benchmark	Feb 4, 2023	Anomaly DetectionChange Point Detection	CodeCode Available	1
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection	Feb 3, 2023	Anomaly DetectionDomain Adaptation	CodeCode Available	1
Laplacian Change Point Detection for Single and Multi-view Dynamic Graphs	Feb 2, 2023	Anomaly DetectionChange Point Detection	CodeCode Available	1

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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