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 3991–4000 of 4856 papers

Title	Date	Tasks	Status	Hype
Using Large-Scale Anomaly Detection on Code to Improve Kotlin Compiler	Apr 3, 2020	Anomaly Detection	CodeCode Available	0
Video Anomaly Detection for Smart Surveillance	Apr 1, 2020	Anomaly DetectionTemporal Localization	—Unverified	0
Anomaly Detection in Univariate Time-series: A Survey on the State-of-the-Art	Apr 1, 2020	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
Learning Memory-guided Normality for Anomaly Detection	Mar 30, 2020	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1
Introduction to Rare-Event Predictive Modeling for Inferential Statisticians -- A Hands-On Application in the Prediction of Breakthrough Patents	Mar 30, 2020	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available	0
SiTGRU: Single-Tunnelled Gated Recurrent Unit for Abnormality Detection	Mar 30, 2020	Anomaly Detection	—Unverified	0
One-Shot GAN Generated Fake Face Detection	Mar 27, 2020	Anomaly DetectionFace Detection	—Unverified	0
ABBA: Adaptive Brownian bridge-based symbolic aggregation of time series	Mar 27, 2020	Anomaly DetectionClustering	—Unverified	0
Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly Detection	Mar 27, 2020	Anomaly DetectionBinary Classification	CodeCode Available	1
FastDTW is approximate and Generally Slower than the Algorithm it Approximates	Mar 25, 2020	Anomaly DetectionClustering	CodeCode Available	1

Show:10 25 50

← PrevPage 400 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