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 3151–3160 of 4856 papers

Title	Date	Tasks	Status
A Video Anomaly Detection Framework based on Appearance-Motion Semantics Representation Consistency	Apr 8, 2022	Anomaly DetectionOptical Flow Estimation	—Unverified
EPASAD: Ellipsoid decision boundary based Process-Aware Stealthy Attack Detector	Apr 8, 2022	Anomaly DetectionIntrusion Detection	—Unverified
Adversarial Machine Learning Attacks Against Video Anomaly Detection Systems	Apr 7, 2022	Anomaly DetectionBIG-bench Machine Learning	—Unverified
Federated Learning for Distributed Spectrum Sensing in NextG Communication Networks	Apr 6, 2022	Anomaly DetectionFederated Learning	—Unverified
Learning to Adapt to Domain Shifts with Few-shot Samples in Anomalous Sound Detection	Apr 5, 2022	Anomaly DetectionDensity Estimation	—Unverified
Do Deep Neural Networks Contribute to Multivariate Time Series Anomaly Detection?	Apr 4, 2022	Anomaly DetectionArticles	—Unverified
Distributed Anomaly Detection and Estimation over Sensor Networks: Observational-Equivalence and Q-Redundant Observer Design	Apr 4, 2022	Anomaly Detection	—Unverified
A Survey on Graph Representation Learning Methods	Apr 4, 2022	Anomaly DetectionGraph Embedding	—Unverified
SAM-kNN Regressor for Online Learning in Water Distribution Networks	Apr 4, 2022	Anomaly Detection	CodeCode Available
Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection	Apr 2, 2022	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available

Show:10 25 50

← PrevPage 316 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	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
7	DDAD	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	PBAS	Detection AUROC	99.8	—	Unverified
10	HETMM	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	DDAD	Detection AUROC	98.9	—	Unverified
5	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	INP-Former ViT-B (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