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 4211–4220 of 4856 papers

Title	Date	Tasks	Status
Can I trust my anomaly detection system? A case study based on explainable AI	Jul 29, 2024	Anomaly Detection	CodeCode Available
Interdependency Matters: Graph Alignment for Multivariate Time Series Anomaly Detection	Oct 11, 2024	Anomaly DetectionTime Series	CodeCode Available
Removing Geometric Bias in One-Class Anomaly Detection with Adaptive Feature Perturbation	Mar 7, 2025	Anomaly DetectionBenchmarking	CodeCode Available
Maximum Entropy Generators for Energy-Based Models	Jan 24, 2019	Anomaly Detection	CodeCode Available
Integrating Quantum-Classical Attention in Patch Transformers for Enhanced Time Series Forecasting	Mar 31, 2025	Anomaly DetectionMultivariate Time Series Forecasting	CodeCode Available
TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly Detection	Nov 29, 2023	Anomaly DetectionComputational Efficiency	CodeCode Available
InQMAD: Incremental Quantum Measurement Anomaly Detection	Oct 11, 2022	Anomaly DetectionDensity Estimation	CodeCode Available
A One-Class Classification method based on Expanded Non-Convex Hulls	Aug 1, 2022	Anomaly DetectionOne-Class Classification	CodeCode Available
Input complexity and out-of-distribution detection with likelihood-based generative models	Sep 25, 2019	Anomaly DetectionOut-of-Distribution Detection	CodeCode Available
Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly Detection	Mar 21, 2024	Anomaly DetectionMedical Image Analysis	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	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