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 101–125 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
MedIAnomaly: A comparative study of anomaly detection in medical images	Apr 6, 2024	Anomaly ClassificationAnomaly Detection	CodeCode Available	2	5
A Multimodal Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational Autoencoder	Nov 2, 2017	Anomaly Detection	CodeCode Available	2	5
A Survey on Diffusion Models for Anomaly Detection	Jan 20, 2025	Anomaly DetectionComputational Efficiency	CodeCode Available	2	5
MemSeg: A semi-supervised method for image surface defect detection using differences and commonalities	May 2, 2022	Anomaly DetectionDefect Detection	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
European Space Agency Benchmark for Anomaly Detection in Satellite Telemetry	Jun 25, 2024	Anomaly DetectionTime Series	CodeCode Available	2	5
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection	Mar 15, 2023	Anomaly DetectionDenoising	CodeCode Available	2	5
Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties	Dec 19, 2024	Anomaly DetectionObject	CodeCode Available	2	5
Odd-One-Out: Anomaly Detection by Comparing with Neighbors	Jun 28, 2024	8kAnomaly Detection	CodeCode Available	2	5
One-for-More: Continual Diffusion Model for Anomaly Detection	Feb 27, 2025	Anomaly Detectioncontinual anomaly detection	CodeCode Available	2	5
DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection	Dec 11, 2023	Anomaly DetectionDenoising	CodeCode Available	2	5
PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series	May 30, 2023	Anomaly DetectionClassification	CodeCode Available	2	5
Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models	May 5, 2025	Anomaly ClassificationAnomaly Detection	CodeCode Available	2	5
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection	Jul 7, 2023	Anomaly DetectionImputation	CodeCode Available	2	5
Registration based Few-Shot Anomaly Detection	Jul 15, 2022	Anomaly Detection	CodeCode Available	2	5
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection	Oct 29, 2023	Anomaly DetectionPrompt Learning	CodeCode Available	2	5
ResAD: A Simple Framework for Class Generalizable Anomaly Detection	Oct 26, 2024	Anomaly Detection	CodeCode Available	2	5
Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding	Feb 13, 2018	Anomaly Detection	CodeCode Available	2	5
CSAD: Unsupervised Component Segmentation for Logical Anomaly Detection	Aug 28, 2024	Anomaly DetectionSegmentation	CodeCode Available	2	5
Self-supervised Anomaly Detection Pretraining Enhances Long-tail ECG Diagnosis	Aug 30, 2024	Anomaly DetectionDiagnostic	CodeCode Available	2	5
Self-Supervised Learning of Time Series Representation via Diffusion Process and Imputation-Interpolation-Forecasting Mask	May 9, 2024	Anomaly DetectionImputation	CodeCode Available	2	5
AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection	May 19, 2025	Anomaly DetectionCode Generation	CodeCode Available	2	5
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection	Jun 17, 2023	Anomaly DetectionContrastive Learning	CodeCode Available	2	5
A Unified Model for Multi-class Anomaly Detection	Jun 8, 2022	Anomaly DetectionAnomaly Localization	CodeCode Available	2	5
Correcting Deviations from Normality: A Reformulated Diffusion Model for Multi-Class Unsupervised Anomaly Detection	Mar 25, 2025	Anomaly DetectionUnsupervised Anomaly Detection	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