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 2241–2250 of 4856 papers

Title	Date	Tasks	Status	Hype
CNTS: Cooperative Network for Time Series	Feb 20, 2023	Anomaly DetectionTime Series	CodeCode Available	0
Anomaly Detection of UAV State Data Based on Single-class Triangular Global Alignment Kernel Extreme Learning Machine	Feb 18, 2023	Anomaly Detection	—Unverified	0
FrAug: Frequency Domain Augmentation for Time Series Forecasting	Feb 18, 2023	Anomaly DetectionData Augmentation	CodeCode Available	1
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images	Feb 18, 2023	Alzheimer's Disease DetectionAnomaly Detection	CodeCode Available	1
DTAAD: Dual Tcn-Attention Networks for Anomaly Detection in Multivariate Time Series Data	Feb 17, 2023	Anomaly DetectionDiagnostic	CodeCode Available	1
Quantile LSTM: A Robust LSTM for Anomaly Detection In Time Series Data	Feb 17, 2023	Anomaly DetectionTime Series	—Unverified	0
Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization	Feb 17, 2023	Anomaly DetectionAnomaly Localization	CodeCode Available	1
A method for incremental discovery of financial event types based on anomaly detection	Feb 16, 2023	Anomaly DetectionDeep Clustering	—Unverified	0
Zero-Shot Anomaly Detection via Batch Normalization	Feb 15, 2023	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	1
A Subspace Projection Approach to Autoencoder-based Anomaly Detection	Feb 15, 2023	Anomaly Detection	—Unverified	0

Show:10 25 50

← PrevPage 225 of 486Next →

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