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 41–50 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Greykite: Deploying Flexible Forecasting at Scale at LinkedIn	Jul 15, 2022	Anomaly DetectionTime Series	CodeCode Available	3	5
AA-CLIP: Enhancing Zero-shot Anomaly Detection via Anomaly-Aware CLIP	Mar 9, 2025	Anomaly DetectionAnomaly Localization	CodeCode Available	3	5
PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection	Apr 8, 2024	Anomaly DetectionLanguage Modeling	CodeCode Available	3	5
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection	Mar 19, 2024	Anomaly DetectionBenchmarking	CodeCode Available	3	5
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection	Apr 9, 2024	Anomaly DetectionDecoder	CodeCode Available	3	5
AdaCLIP: Adapting CLIP with Hybrid Learnable Prompts for Zero-Shot Anomaly Detection	Jul 22, 2024	Anomaly DetectionLanguage Modeling	CodeCode Available	3	5
3CAD: A Large-Scale Real-World 3C Product Dataset for Unsupervised Anomaly	Feb 9, 2025	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	2	5
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection	Mar 15, 2023	Anomaly DetectionDenoising	CodeCode Available	2	5
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding	Feb 13, 2018	Anomaly Detection	CodeCode Available	2	5
AnoDDPM: Anomaly Detection With Denoising Diffusion Probabilistic Models Using Simplex Noise	Jun 30, 2022	Anomaly DetectionDenoising	CodeCode Available	2	5

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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