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 1661–1670 of 4856 papers

Title	Date	Tasks	Status
Data-Efficient Methods for Dialogue Systems	Dec 5, 2020	Anomaly DetectionData Augmentation	—Unverified
Anomaly Rule Detection in Sequence Data	Nov 29, 2021	Anomaly DetectionOutlier Detection	—Unverified
Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound	Jul 21, 2024	Anomaly DetectionDenoising	—Unverified
A Scalable k-Medoids Clustering via Whale Optimization Algorithm	Aug 30, 2024	Anomaly DetectionClustering	—Unverified
An Adaptive Training-less System for Anomaly Detection in Crowd Scenes	Jun 3, 2019	Anomaly Detectionobject-detection	—Unverified
Effort-free Automated Skeletal Abnormality Detection of Rat Fetuses on Whole-body Micro-CT Scans	Jun 3, 2021	Anomaly DetectionBIG-bench Machine Learning	—Unverified
End-to-End Abnormality Detection in Medical Imaging	Jan 1, 2018	Anomaly DetectionComputed Tomography (CT)	—Unverified
Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysis	Nov 5, 2024	Anomaly DetectionComputational Efficiency	—Unverified
Digraphwave: Scalable Extraction of Structural Node Embeddings via Diffusion on Directed Graphs	Jul 20, 2022	Anomaly DetectionNode Classification	—Unverified
Data-Efficient and Interpretable Tabular Anomaly Detection	Mar 3, 2022	Additive modelsAnomaly Detection	—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	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