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 51–60 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection	Oct 29, 2023	Anomaly DetectionPrompt Learning	CodeCode Available	2	5
DualAnoDiff: Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation	Aug 24, 2024	Anomaly ClassificationAnomaly Detection	CodeCode Available	2	5
FITS: Modeling Time Series with 10k Parameters	Jul 6, 2023	Anomaly DetectionTime Series	CodeCode Available	2	5
DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection	Dec 11, 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
dtaianomaly: A Python library for time series anomaly detection	Feb 20, 2025	Anomaly DetectionTime Series	CodeCode Available	2	5
Dual Conditioned Motion Diffusion for Pose-Based Video Anomaly Detection	Dec 23, 2024	Anomaly DetectionVideo Anomaly Detection	CodeCode Available	2	5
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies	Mar 25, 2023	Anomaly DetectionComputational Efficiency	CodeCode Available	2	5
Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation	May 14, 2025	Anomaly ClassificationAnomaly Detection	CodeCode Available	2	5
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection	Mar 15, 2023	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	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