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 241–250 of 4856 papers

Title	Date	Tasks	Status	Hype
Deep Learning in Latent Space for Video Prediction and Compression	Jun 19, 2021	Anomaly DetectionDeep Learning	CodeCode Available	1
Deep Reinforcement Learning for Cost-Effective Medical Diagnosis	Feb 20, 2023	Anomaly DetectionDeep Reinforcement Learning	CodeCode Available	1
ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection	Dec 22, 2023	Anomaly DetectionFraud Detection	CodeCode Available	1
DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic	Aug 26, 2020	Action RecognitionAnomaly Detection	CodeCode Available	1
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly Localization	Jun 9, 2022	Anomaly DetectionAnomaly Localization	CodeCode Available	1
Challenging Current Semi-Supervised Anomaly Segmentation Methods for Brain MRI	Sep 13, 2021	Anomaly DetectionAnomaly Segmentation	CodeCode Available	1
Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events	Aug 27, 2020	Anomaly DetectionCloze Test	CodeCode Available	1
Demystifying and Extracting Fault-indicating Information from Logs for Failure Diagnosis	Sep 20, 2024	Anomaly DetectionFault Diagnosis	CodeCode Available	1
DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognition	Jul 6, 2022	Anomaly DetectionOpen Set Learning	CodeCode Available	1
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly Detection	Aug 18, 2023	Anomaly DetectionContrastive Learning	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	HETMM	Detection AUROC	99.8	—	Unverified
7	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	PBAS	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	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	DDAD	Detection AUROC	98.9	—	Unverified
6	Dinomaly ViT-L (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