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 4776–4800 of 4856 papers

Title	Date	Tasks	Status
Confidence-Aware and Self-Supervised Image Anomaly Localisation	Mar 23, 2023	Anomaly DetectionMedical Image Analysis	CodeCode Available
Anomaly Detection in Cooperative Vehicle Perception Systems under Imperfect Communication	Jan 28, 2025	Anomaly ClassificationAnomaly Detection	CodeCode Available
TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly Detection	Apr 3, 2024	Anomaly DetectionData Augmentation	CodeCode Available
A Taxonomy of Network Threats and the Effect of Current Datasets on Intrusion Detection Systems	Jun 9, 2018	Anomaly DetectionIntrusion Detection	CodeCode Available
Towards frugal unsupervised detection of subtle abnormalities in medical imaging	Sep 4, 2023	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available
ENCODE: Encoding NetFlows for Network Anomaly Detection	Jul 8, 2022	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available
Prompt-Enhanced Multiple Instance Learning for Weakly Supervised Video Anomaly Detection	Jan 1, 2024	Anomaly DetectionMultiple Instance Learning	CodeCode Available
PromptTAD: Object-Prompt Enhanced Traffic Anomaly Detection	May 22, 2025	Anomaly DetectionObject	CodeCode Available
Unsupervised Anomaly Detection Ensembles using Item Response Theory	Jun 11, 2021	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available
Concept Drift and Anomaly Detection in Graph Streams	Jun 21, 2017	Anomaly DetectionChange Detection	CodeCode Available
A Survey on GANs for Anomaly Detection	Jun 27, 2019	Anomaly DetectionSurvey	CodeCode Available
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning	Aug 8, 2024	3D Anomaly DetectionAnomaly Detection	CodeCode Available
Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure	Mar 19, 2025	Anomaly DetectionComputational Efficiency	CodeCode Available
A Subspace Method for Time Series Anomaly Detection in Cyber-Physical Systems	May 20, 2022	Anomaly DetectionTime Series	CodeCode Available
Concentration Inequalities for Two-Sample Rank Processes with Application to Bipartite Ranking	Apr 7, 2021	Anomaly DetectionInformation Retrieval	CodeCode Available
Pseudo-healthy synthesis with pathology disentanglement and adversarial learning	Apr 20, 2020	Anomaly DetectionDisentanglement	CodeCode Available
Concentration bounds for the empirical angular measure with statistical learning applications	Apr 7, 2021	Anomaly DetectionBinary Classification	CodeCode Available
Computer Vision and Normalizing Flow-Based Defect Detection	Dec 12, 2020	Anomaly DetectionDefect Detection	CodeCode Available
Learning Invariant Rules from Data for Interpretable Anomaly Detection	Nov 24, 2022	Anomaly DetectionDecision Making	CodeCode Available
Interpreting Vulnerabilities of Multi-Instance Learning to Adversarial Perturbations	Nov 30, 2022	Anomaly DetectionImage Classification	CodeCode Available
Enabling Efficient and Flexible Interpretability of Data-driven Anomaly Detection in Industrial Processes with AcME-AD	Apr 29, 2024	Anomaly Detection	CodeCode Available
Addressing the Impact of Localized Training Data in Graph Neural Networks	Jul 24, 2023	Anomaly DetectionGraph Generation	CodeCode Available
Anomaly Detection: How to Artificially Increase your F1-Score with a Biased Evaluation Protocol	Jun 30, 2021	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available
ALFA: A Dataset for UAV Fault and Anomaly Detection	Jul 14, 2019	Anomaly DetectionFault Detection	CodeCode Available
Zero-bias Deep Learning Enabled Quick and Reliable Abnormality Detection in IoT	Apr 8, 2021	Anomaly DetectionChange Point Detection	CodeCode Available

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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