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 3641–3650 of 4856 papers

Title	Date	Tasks	Status
Efficient Nonlinear RX Anomaly Detectors	Dec 7, 2020	Anomaly Detection	—Unverified
Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications	Dec 7, 2020	Anomaly DetectionExplainable Recommendation	—Unverified
Perfect density models cannot guarantee anomaly detection	Dec 7, 2020	Active LearningAnomaly Detection	—Unverified
No Need to Know Physics: Resilience of Process-based Model-free Anomaly Detection for Industrial Control Systems	Dec 7, 2020	Anomaly Detection	—Unverified
Data-Efficient Methods for Dialogue Systems	Dec 5, 2020	Anomaly DetectionData Augmentation	—Unverified
Deep Learning for Medical Anomaly Detection -- A Survey	Dec 4, 2020	Anomaly DetectionDeep Learning	—Unverified
Video Anomaly Detection by Estimating Likelihood of Representations	Dec 2, 2020	Action RecognitionAnomaly Detection	CodeCode Available
Unsupervised Anomaly Detection From Semantic Similarity Scores	Dec 1, 2020	Anomaly DetectionOut-of-Distribution Detection	—Unverified
Timeseries Anomaly Detection using Temporal Hierarchical One-Class Network	Dec 1, 2020	Anomaly DetectionClustering	—Unverified
Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks	Dec 1, 2020	Anomaly DetectionImputation	—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	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