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 1861–1870 of 4856 papers

Title	Date	Tasks	Status	Hype
Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies	Aug 15, 2023	Anomaly DetectionLog Parsing	CodeCode Available	1
ImbSAM: A Closer Look at Sharpness-Aware Minimization in Class-Imbalanced Recognition	Aug 15, 2023	Anomaly DetectionSemi-supervised Anomaly Detection	CodeCode Available	1
Future Video Prediction from a Single Frame for Video Anomaly Detection	Aug 15, 2023	Anomaly DetectionPrediction	—Unverified	0
Searching for Novel Chemistry in Exoplanetary Atmospheres using Machine Learning for Anomaly Detection	Aug 15, 2023	Anomaly DetectionNovelty Detection	—Unverified	0
A Graph Encoder-Decoder Network for Unsupervised Anomaly Detection	Aug 15, 2023	Anomaly DetectionDecoder	—Unverified	0
Digital Twin of the Radio Environment: A Novel Approach for Anomaly Detection in Wireless Networks	Aug 14, 2023	Anomaly Detection	CodeCode Available	0
Survey on video anomaly detection in dynamic scenes with moving cameras	Aug 14, 2023	Anomaly DetectionSurvey	—Unverified	0
SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection	Aug 13, 2023	Anomaly DetectionIntrusion Detection	—Unverified	0
Target before Shooting: Accurate Anomaly Detection and Localization under One Millisecond via Cascade Patch Retrieval	Aug 13, 2023	Anomaly DetectionSupervised Anomaly Detection	CodeCode Available	1
ALGAN: Time Series Anomaly Detection with Adjusted-LSTM GAN	Aug 13, 2023	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	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