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 711–720 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Hard-normal Example-aware Template Mutual Matching for Industrial Anomaly Detection	Mar 28, 2023	Anomaly DetectionAnomaly Localization	CodeCode Available	1	5
DeepTrust: A Reliable Financial Knowledge Retrieval Framework For Explaining Extreme Pricing Anomalies	Mar 11, 2022	Anomaly DetectionInformation Retrieval	CodeCode Available	1	5
ADGym: Design Choices for Deep Anomaly Detection	Sep 27, 2023	Anomaly DetectionCloud Computing	CodeCode Available	1	5
DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognition	Jul 6, 2022	Anomaly DetectionOpen Set Learning	CodeCode Available	1	5
DEGAN: Time Series Anomaly Detection using Generative Adversarial Network Discriminators and Density Estimation	Oct 5, 2022	Anomaly DetectionDensity Estimation	CodeCode Available	1	5
Networking Systems for Video Anomaly Detection: A Tutorial and Survey	May 16, 2024	Anomaly DetectionEdge-computing	CodeCode Available	1	5
Delving into CLIP latent space for Video Anomaly Recognition	Oct 4, 2023	Anomaly DetectionMultiple Instance Learning	CodeCode Available	1	5
Demystifying and Extracting Fault-indicating Information from Logs for Failure Diagnosis	Sep 20, 2024	Anomaly DetectionFault Diagnosis	CodeCode Available	1	5
Anomaly Detection in Emails using Machine Learning and Header Information	Mar 19, 2022	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available	1	5
Graph Neural Networks based Log Anomaly Detection and Explanation	Jul 2, 2023	Anomaly DetectionGraph Neural Network	CodeCode Available	1	5

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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