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 1241–1250 of 4856 papers

Title	Date	Tasks	Status	Hype
Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling	Apr 27, 2024	Anomaly DetectionImage Reconstruction	—Unverified	0
Accurate and fast anomaly detection in industrial processes and IoT environments	Apr 27, 2024	Anomaly DetectionFeature Importance	—Unverified	0
Domain Adaptive and Fine-grained Anomaly Detection for Single-cell Sequencing Data and Beyond	Apr 26, 2024	Anomaly DetectionCell Detection	CodeCode Available	0
Frequency-Guided Multi-Level Human Action Anomaly Detection with Normalizing Flows	Apr 26, 2024	Anomaly Detection	—Unverified	0
Synchronized Stepwise Control of Firing and Learning Thresholds in a Spiking Randomly Connected Neural Network toward Hardware Implementation	Apr 26, 2024	Anomaly Detection	—Unverified	0
Dr-SAM: An End-to-End Framework for Vascular Segmentation, Diameter Estimation, and Anomaly Detection on Angiography Images	Apr 25, 2024	Anomaly DetectionDiagnostic	CodeCode Available	1
Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection	Apr 25, 2024	Anomaly DetectionGraph Anomaly Detection	—Unverified	0
Anomaly Detection for Incident Response at Scale	Apr 24, 2024	Anomaly DetectionDrift Detection	—Unverified	0
ABCD: Trust enhanced Attention based Convolutional Autoencoder for Risk Assessment	Apr 24, 2024	Anomaly Detection	—Unverified	0
S2DEVFMAP: Self-Supervised Learning Framework with Dual Ensemble Voting Fusion for Maximizing Anomaly Prediction in Timeseries	Apr 24, 2024	Anomaly DetectionSelf-Supervised Learning	—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