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 3791–3800 of 4856 papers

Title	Date	Tasks	Status	Hype
Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events	Aug 27, 2020	Anomaly DetectionCloze Test	CodeCode Available	1
Defending Water Treatment Networks: Exploiting Spatio-temporal Effects for Cyber Attack Detection	Aug 26, 2020	Anomaly DetectionAttribute	—Unverified	0
DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic	Aug 26, 2020	Action RecognitionAnomaly Detection	CodeCode Available	1
Applying Surface Normal Information in Drivable Area and Road Anomaly Detection for Ground Mobile Robots	Aug 26, 2020	Anomaly DetectionSegmentation	CodeCode Available	1
Hybrid Deep Neural Networks to Infer State Models of Black-Box Systems	Aug 26, 2020	Anomaly DetectionC++ code	CodeCode Available	0
Automated Model Selection for Time-Series Anomaly Detection	Aug 25, 2020	Anomaly Detectionmodel	—Unverified	0
USAD: UnSupervised Anomaly Detection on Multivariate Time Series	Aug 23, 2020	Anomaly DetectionTime Series	CodeCode Available	1
ADIC: Anomaly Detection Integrated Circuit in 65nm CMOS utilizing Approximate Computing	Aug 21, 2020	Anomaly DetectionOne-class classifier	—Unverified	0
Self-Attentive Classification-Based Anomaly Detection in Unstructured Logs	Aug 21, 2020	Anomaly DetectionClassification	—Unverified	0
TAnoGAN: Time Series Anomaly Detection with Generative Adversarial Networks	Aug 21, 2020	Anomaly DetectionTime Series	CodeCode Available	1

Show:10 25 50

← PrevPage 380 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