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 3891–3900 of 4856 papers

Title	Date	Tasks	Status	Hype
A specifically designed machine learning algorithm for GNSS position time series prediction and its applications in outlier and anomaly detection and earthquake prediction	Jun 16, 2020	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
Plug-and-Play Anomaly Detection with Expectation Maximization Filtering	Jun 16, 2020	Anomaly Detection	—Unverified	0
A Taxonomy and Review of Algorithms for Modeling and Predicting Human Driver Behavior	Jun 15, 2020	Anomaly Detectionmotion prediction	—Unverified	0
Anomalous Motion Detection on Highway Using Deep Learning	Jun 15, 2020	Anomaly DetectionDeep Learning	CodeCode Available	0
Learning Latent Space Energy-Based Prior Model	Jun 15, 2020	Anomaly Detectionmodel	CodeCode Available	1
Robust Variational Autoencoder for Tabular Data with Beta Divergence	Jun 15, 2020	Anomaly DetectionData Poisoning	—Unverified	0
Categorical anomaly detection in heterogeneous data using minimum description length clustering	Jun 14, 2020	Anomaly DetectionClustering	—Unverified	0
Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation	Jun 12, 2020	Anomaly DetectionDensity Ratio Estimation	CodeCode Available	0
COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature	Jun 11, 2020	Anomaly DetectionArticles	CodeCode Available	1
Joint Training of Variational Auto-Encoder and Latent Energy-Based Model	Jun 10, 2020	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	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