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 741–750 of 4856 papers

Title	Date	Tasks	Status	Hype
C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting	Dec 22, 2023	Anomaly DetectionTime Series	CodeCode Available	1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly Detection	Aug 19, 2022	Anomaly DetectionRepresentation Learning	CodeCode Available	1
Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcity	May 29, 2020	Active LearningAnomaly Detection	CodeCode Available	1
MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly Detection	Feb 24, 2025	AnatomyAnomaly Detection	CodeCode Available	1
Building an Automated and Self-Aware Anomaly Detection System	Nov 10, 2020	Anomaly DetectionTime Series	CodeCode Available	1
MAEDAY: MAE for few and zero shot AnomalY-Detection	Nov 25, 2022	Anomaly DetectionImage Inpainting	CodeCode Available	1
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection	Mar 10, 2022	3D Anomaly Detection3D Anomaly Detection and Segmentation	CodeCode Available	1
CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset	Sep 30, 2024	Anomaly Detection	CodeCode Available	1
Masked Autoencoders for Unsupervised Anomaly Detection in Medical Images	Jul 14, 2023	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	1
Broiler-Net: A Deep Convolutional Framework for Broiler Behavior Analysis in Poultry Houses	Jan 22, 2024	Anomaly Detection	CodeCode Available	1

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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