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 3081–3090 of 4856 papers

Title	Date	Tasks	Status	Hype
Efficient Non-Compression Auto-Encoder for Driving Noise-based Road Surface Anomaly Detection	Nov 22, 2021	Anomaly DetectionFriction	—Unverified	0
Effect of Deep Transfer and Multi task Learning on Sperm Abnormality Detection	Nov 21, 2021	Anomaly DetectionMulti-Task Learning	CodeCode Available	0
UN-AVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring	Nov 19, 2021	Anomaly DetectionData Visualization	CodeCode Available	0
DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behavior	Nov 18, 2021	Anomaly DetectionAutonomous Driving	—Unverified	0
LAnoBERT: System Log Anomaly Detection based on BERT Masked Language Model	Nov 18, 2021	Anomaly DetectionLanguage Modeling	—Unverified	0
Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection	Nov 17, 2021	Anomaly DetectionOne-Class Classification	CodeCode Available	1
Online Self-Evolving Anomaly Detection in Cloud Computing Environments	Nov 16, 2021	Anomaly DetectionCloud Computing	CodeCode Available	0
UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection	Nov 16, 2021	Action RecognitionAnomaly Detection	CodeCode Available	1
Learning Graph Neural Networks for Multivariate Time Series Anomaly Detection	Nov 15, 2021	Anomaly DetectionTime Series	CodeCode Available	1
FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows	Nov 15, 2021	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	1

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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