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 3361–3370 of 4856 papers

Title	Date	Tasks	Status
Training-Free Time-Series Anomaly Detection: Leveraging Image Foundation Models	Aug 27, 2024	Anomaly DetectionTime Series	—Unverified
Training Medical Large Vision-Language Models with Abnormal-Aware Feedback	Jan 2, 2025	Anomaly DetectionVisual Localization	—Unverified
Training robust anomaly detection using ML-Enhanced simulations	Aug 27, 2020	Anomaly Detection	—Unverified
Transcriptional Response of SK-N-AS Cells to Methamidophos	Aug 11, 2019	Anomaly DetectionCausal Inference	—Unverified
Transfer Anomaly Detection by Inferring Latent Domain Representations	Dec 1, 2019	Anomaly Detection	—Unverified
Transfer learning applications for anomaly detection in wind turbines	Apr 3, 2024	Anomaly DetectionDecoder	—Unverified
Transfer Learning as an Essential Tool for Digital Twins in Renewable Energy Systems	Mar 9, 2022	Anomaly DetectionTransfer Learning	—Unverified
Transfer Learning from an Auxiliary Discriminative Task for Unsupervised Anomaly Detection	Dec 5, 2019	Anomaly DetectionFeature Engineering	—Unverified
Transfer Learning Gaussian Anomaly Detection by Fine-tuning Representations	Aug 9, 2021	Anomaly DetectionAnomaly Segmentation	—Unverified
Unsupervised Transfer Learning for Anomaly Detection: Application to Complementary Operating Condition Transfer	Aug 18, 2020	Anomaly DetectionClustering	—Unverified

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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