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 861–870 of 4856 papers

Title	Date	Tasks	Status	Hype	Score
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection	Dec 23, 2024	Anomaly DetectionPrompt Learning	CodeCode Available	1	5
The MVTec 3D-AD Dataset for Unsupervised 3D Anomaly Detection and Localization	Dec 16, 2021	3D Anomaly Detection and SegmentationAnomaly Detection	CodeCode Available	1	5
KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks	Nov 1, 2024	Anomaly DetectionKolmogorov-Arnold Networks	CodeCode Available	1	5
GLAD: GLocalized Anomaly Detection via Human-in-the-Loop Learning	Oct 2, 2018	Anomaly Detection	CodeCode Available	1	5
Label-Free Multivariate Time Series Anomaly Detection	Dec 17, 2023	Anomaly DetectionDensity Estimation	CodeCode Available	1	5
A Survey of Visual Sensory Anomaly Detection	Feb 14, 2022	Anomaly DetectionSurvey	CodeCode Available	1	5
A Survey of World Models for Autonomous Driving	Jan 20, 2025	Anomaly DetectionAutonomous Driving	CodeCode Available	1	5
Asymmetric Student-Teacher Networks for Industrial Anomaly Detection	Oct 14, 2022	3D Anomaly DetectionAnomaly Detection	CodeCode Available	1	5
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows	Jul 27, 2021	Anomaly ClassificationAnomaly Detection	CodeCode Available	1	5
Iterative weak/self-supervised classification framework for abnormal events detection	Jan 3, 2021	Abnormal Event Detection In VideoAnomaly Detection	CodeCode Available	1	5

Show:10 25 50

← PrevPage 87 of 486Next →

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