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 2971–2980 of 4856 papers

Title	Date	Tasks	Status
Robust Anomaly Detection in Images using Adversarial Autoencoders	Jan 18, 2019	Anomaly DetectionMedical Image Analysis	—Unverified
Robust Anomaly Detection in Network Traffic: Evaluating Machine Learning Models on CICIDS2017	Jun 23, 2025	Anomaly DetectionIntrusion Detection	—Unverified
Robust Anomaly Detection Using Semidefinite Programming	Apr 3, 2015	Anomaly Detection	—Unverified
Robust Attack Detection Approach for IIoT Using Ensemble Classifier	Jan 30, 2021	Anomaly DetectionIntrusion Detection	—Unverified
Robust Audio Anomaly Detection	Feb 3, 2022	Anomaly DetectionTime Series	—Unverified
Robust Distribution Alignment for Industrial Anomaly Detection under Distribution Shift	Mar 19, 2025	3D Anomaly DetectionAnomaly Detection	—Unverified
Robust Errant Beam Prognostics with Conditional Modeling for Particle Accelerators	Nov 22, 2023	Anomaly Detection	—Unverified
Robust Learning of Deep Time Series Anomaly Detection Models with Contaminated Training Data	Aug 3, 2022	Anomaly DetectionTime Series	—Unverified
Robustness of ML-Enhanced IDS to Stealthy Adversaries	Apr 21, 2021	Anomaly DetectionIntrusion Detection	—Unverified
Robustness Testing of Data and Knowledge Driven Anomaly Detection in Cyber-Physical Systems	Apr 20, 2022	Anomaly Detectionimage-classification	—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	UniNet	Detection AUROC	99.9	—	Unverified
5	GLASS	Detection AUROC	99.9	—	Unverified
6	PBAS	Detection AUROC	99.8	—	Unverified
7	HETMM	Detection AUROC	99.8	—	Unverified
8	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	EfficientAD (early stopping)	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	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	DDAD	Detection AUROC	98.9	—	Unverified
7	GLASS	Detection AUROC	98.8	—	Unverified
8	DiffusionAD	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