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 3041–3050 of 4856 papers

Title	Date	Tasks	Status	Hype
Anomaly Crossing: New Horizons for Video Anomaly Detection as Cross-domain Few-shot Learning	Dec 12, 2021	Anomaly DetectionCross-Domain Few-Shot	—Unverified	0
DeepFIB: Self-Imputation for Time Series Anomaly Detection	Dec 12, 2021	Anomaly DetectionAnomaly Localization	—Unverified	0
Fast and scalable neuroevolution deep learning architecture search for multivariate anomaly detection	Dec 10, 2021	Anomaly DetectionEvolutionary Algorithms	—Unverified	0
LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks	Dec 10, 2021	Anomaly DetectionGraph Neural Network	CodeCode Available	1
Multimedia Datasets for Anomaly Detection: A Review	Dec 10, 2021	Anomaly Detectionobject-detection	—Unverified	0
Discrete neural representations for explainable anomaly detection	Dec 10, 2021	Anomaly DetectionObject	—Unverified	0
PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures	Dec 9, 2021	Adversarial RobustnessAnomaly Detection	CodeCode Available	1
Ymir: A Supervised Ensemble Framework for Multivariate Time Series Anomaly Detection	Dec 9, 2021	Anomaly DetectionEnsemble Learning	—Unverified	0
Transformaly -- Two (Feature Spaces) Are Better Than One	Dec 8, 2021	Anomaly DetectionVocal Bursts Valence Prediction	CodeCode Available	1
A Hierarchical Spatio-Temporal Graph Convolutional Neural Network for Anomaly Detection in Videos	Dec 8, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	—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