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 3321–3330 of 4856 papers

Title	Date	Tasks	Status	Hype
X-MAN: Explaining multiple sources of anomalies in video	Jun 16, 2021	Anomaly DetectionDecision Making	—Unverified	0
FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformation	Jun 16, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1
Towards Total Recall in Industrial Anomaly Detection	Jun 15, 2021	3D Anomaly DetectionAnomaly Classification	CodeCode Available	2
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection	Jun 15, 2021	Anomaly DetectionFederated Learning	CodeCode Available	1
Multivariate Business Process Representation Learning utilizing Gramian Angular Fields and Convolutional Neural Networks	Jun 15, 2021	Anomaly DetectionClustering	—Unverified	0
Time Series Anomaly Detection for Cyber-Physical Systems via Neural System Identification and Bayesian Filtering	Jun 15, 2021	Anomaly DetectionTime Series	CodeCode Available	1
MLPerf Tiny Benchmark	Jun 14, 2021	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available	1
A Comprehensive Survey on Graph Anomaly Detection with Deep Learning	Jun 14, 2021	Anomaly DetectionDeep Learning	CodeCode Available	1
Inverting Adversarially Robust Networks for Image Synthesis	Jun 13, 2021	Anomaly DetectionDeep Feature Inversion	CodeCode Available	0
RadArnomaly: Protecting Radar Systems from Data Manipulation Attacks	Jun 13, 2021	Anomaly Detection	—Unverified	0

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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