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 81–90 of 4856 papers

Title	Date	Tasks	Status	Hype
LogLLM: Log-based Anomaly Detection Using Large Language Models	Nov 13, 2024	Anomaly DetectionDecoder	CodeCode Available	2
A Survey on RGB, 3D, and Multimodal Approaches for Unsupervised Industrial Anomaly Detection	Oct 29, 2024	Anomaly Detection	CodeCode Available	2
ResAD: A Simple Framework for Class Generalizable Anomaly Detection	Oct 26, 2024	Anomaly Detection	CodeCode Available	2
AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios	Oct 18, 2024	Anomaly ClassificationAnomaly Detection	CodeCode Available	2
CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patching	Oct 16, 2024	Anomaly DetectionTime Series	CodeCode Available	2
PointAD: Comprehending 3D Anomalies from Points and Pixels for Zero-shot 3D Anomaly Detection	Oct 1, 2024	3D Anomaly DetectionAnomaly Detection	CodeCode Available	2
Towards Zero-shot Point Cloud Anomaly Detection: A Multi-View Projection Framework	Sep 20, 2024	Anomaly DetectionSpecificity	CodeCode Available	2
Self-supervised Anomaly Detection Pretraining Enhances Long-tail ECG Diagnosis	Aug 30, 2024	Anomaly DetectionDiagnostic	CodeCode Available	2
CSAD: Unsupervised Component Segmentation for Logical Anomaly Detection	Aug 28, 2024	Anomaly DetectionSegmentation	CodeCode Available	2
DualAnoDiff: Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation	Aug 24, 2024	Anomaly ClassificationAnomaly Detection	CodeCode Available	2

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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	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
7	DDAD	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	PBAS	Detection AUROC	99.8	—	Unverified
10	HETMM	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	DDAD	Detection AUROC	98.9	—	Unverified
5	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	INP-Former ViT-B (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