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 1971–1980 of 4856 papers

Title	Date	Tasks	Status
Anomaly Detection with Prototype-Guided Discriminative Latent Embeddings	Apr 30, 2021	Anomaly DetectionOptical Flow Estimation	—Unverified
Explainable Machine Learning-Based Security and Privacy Protection Framework for Internet of Medical Things Systems	Mar 14, 2024	Anomaly DetectionExplainable artificial intelligence	—Unverified
Few-shot Anomaly Detection in Text with Deviation Learning	Aug 22, 2023	Anomaly DetectionFew-Shot Learning	—Unverified
Explainable multi-class anomaly detection on functional data	May 3, 2022	Anomaly DetectionMulti-class Anomaly Detection	—Unverified
A Virtual Testbed for Critical Incident Investigation with Autonomous Remote Aerial Vehicle Surveying, Artificial Intelligence, and Decision Support	Sep 14, 2018	Anomaly DetectionRetrieval	—Unverified
Explainable Transformer-Based Anomaly Detection for Internet of Things Security Check for updates	Jan 5, 2024	Anomaly Detectionenergy management	—Unverified
Explainable Unsupervised Anomaly Detection with Random Forest	Apr 22, 2025	Anomaly DetectionFeature Importance	—Unverified
Explained anomaly detection in text reviews: Can subjective scenarios be correctly evaluated?	Nov 8, 2023	Anomaly Detection	—Unverified
A Vision Inspired Neural Network for Unsupervised Anomaly Detection in Unordered Data	May 13, 2022	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
Cross-Modal Fusion and Attention Mechanism for Weakly Supervised Video Anomaly Detection	Dec 29, 2024	Anomaly DetectionGraph Attention	—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