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 661–670 of 4856 papers

Title	Date	Tasks	Status	Hype
Continual Learning for Unsupervised Anomaly Detection in Continuous Auditing of Financial Accounting Data	Dec 25, 2021	Anomaly Detectioncontinual anomaly detection	CodeCode Available	1
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types	Dec 21, 2021	Anomaly DetectionClustering	CodeCode Available	1
Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation	Dec 19, 2021	Anomaly DetectionKnowledge Distillation	CodeCode Available	1
The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization	Dec 16, 2021	3D Anomaly Detection and SegmentationAnomaly Detection	CodeCode Available	1
LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks	Dec 10, 2021	Anomaly DetectionGraph Neural Network	CodeCode Available	1
PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures	Dec 9, 2021	Adversarial RobustnessAnomaly Detection	CodeCode Available	1
Transformaly -- Two (Feature Spaces) Are Better Than One	Dec 8, 2021	Anomaly DetectionVocal Bursts Valence Prediction	CodeCode Available	1
Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection	Dec 7, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive Learning	Dec 6, 2021	Anomaly DetectionContrastive Learning	CodeCode Available	1
Anomaly Detection of Wind Turbine Time Series using Variational Recurrent Autoencoders	Dec 5, 2021	Anomaly DetectionTime Series	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	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