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 3671–3680 of 4856 papers

Title	Date	Tasks	Status	Hype
Real-World Anomaly Detection by using Digital Twin Systems and Weakly-Supervised Learning	Nov 12, 2020	Anomaly DetectionClustering	—Unverified	0
Image Anomaly Detection by Aggregating Deep Pyramidal Representations	Nov 12, 2020	Anomaly Detection	—Unverified	0
A Transfer Learning Framework for Anomaly Detection Using Model of Normality	Nov 12, 2020	Anomaly DetectionTransfer Learning	—Unverified	0
Testing for Typicality with Respect to an Ensemble of Learned Distributions	Nov 11, 2020	Anomaly Detection	—Unverified	0
Statistical learning for change point and anomaly detection in graphs	Nov 10, 2020	Anomaly Detection	—Unverified	0
Self-Supervised Out-of-Distribution Detection in Brain CT Scans	Nov 10, 2020	Anomaly DetectionOut-of-Distribution Detection	—Unverified	0
Decoupled Appearance and Motion Learning for Efficient Anomaly Detection in Surveillance Video	Nov 10, 2020	Anomaly Detection	CodeCode Available	0
Building an Automated and Self-Aware Anomaly Detection System	Nov 10, 2020	Anomaly DetectionTime Series	CodeCode Available	1
F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams	Nov 9, 2020	Anomaly DetectionAnomaly Detection in Edge Streams	CodeCode Available	1
Distance-Based Anomaly Detection for Industrial Surfaces Using Triplet Networks	Nov 9, 2020	Anomaly DetectionTriplet	—Unverified	0

Show:10 25 50

← PrevPage 368 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	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