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 3131–3140 of 4856 papers

Title	Date	Tasks	Status	Hype
Learning Not to Reconstruct Anomalies	Oct 19, 2021	Anomaly DetectionOne-Class Classification	CodeCode Available	1
Memory-augmented Adversarial Autoencoders for Multivariate Time-series Anomaly Detection with Deep Reconstruction and Prediction	Oct 15, 2021	Anomaly DetectionTime Series	—Unverified	0
Anomaly Detection in Multi-Agent Trajectories for Automated Driving	Oct 15, 2021	Anomaly Detection	CodeCode Available	1
A Semi-Supervised Approach for Abnormal Event Prediction on Large Operational Network Time-Series Data	Oct 14, 2021	Anomaly DetectionEvent Detection	—Unverified	0
Challenges for Unsupervised Anomaly Detection in Particle Physics	Oct 13, 2021	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified	0
Deep Video Anomaly Detection: Opportunities and Challenges	Oct 11, 2021	Anomaly DetectionDeep Learning	—Unverified	0
A Survey on Proactive Customer Care: Enabling Science and Steps to Realize it	Oct 11, 2021	Anomaly DetectionSurvey	—Unverified	0
Multi-branch Neural Networks for Video Anomaly Detection in Adverse Lighting and Weather Conditions	Oct 10, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	—Unverified	0
Focus Your Distribution: Coarse-to-Fine Non-Contrastive Learning for Anomaly Detection and Localization	Oct 9, 2021	Anomaly DetectionContrastive Learning	—Unverified	0
Hankel-structured Tensor Robust PCA for Multivariate Traffic Time Series Anomaly Detection	Oct 8, 2021	Anomaly DetectionTime Series	—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