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 2831–2840 of 4856 papers

Title	Date	Tasks	Status
Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore	Jan 28, 2023	Anomaly Detection	—Unverified
Putting Sarcasm Detection into Context: The Effects of Class Imbalance and Manual Labelling on Supervised Machine Classification of Twitter Conversations	Aug 1, 2016	Anomaly DetectionGeneral Classification	—Unverified
PV Fleet Modeling via Smooth Periodic Gaussian Copula	Jun 5, 2023	Anomaly DetectionTime Series	—Unverified
PV-VTT: A Privacy-Centric Dataset for Mission-Specific Anomaly Detection and Natural Language Interpretation	Oct 30, 2024	Anomaly DetectionDescriptive	—Unverified
PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection	Dec 11, 2024	Anomaly DetectionFraud Detection	—Unverified
PyramidFlow: High-Resolution Defect Contrastive Localization using Pyramid Normalizing Flow	Mar 5, 2023	Anomaly DetectionVocal Bursts Intensity Prediction	—Unverified
QANet: Tensor Decomposition Approach for Query-based Anomaly Detection in Heterogeneous Information Networks	Oct 19, 2018	Anomaly DetectionClustering	—Unverified
Q-MIND: Defeating Stealthy DoS Attacks in SDN with a Machine-learning based Defense Framework	Jul 27, 2019	Anomaly DetectionBIG-bench Machine Learning	—Unverified
Qsco: A Quantum Scoring Module for Open-set Supervised Anomaly Detection	May 25, 2024	Anomaly DetectionSupervised Anomaly Detection	—Unverified
Quality In / Quality Out: Data quality more relevant than model choice in anomaly detection with the UGR'16	May 31, 2023	Anomaly Detection	—Unverified

Show:10 25 50

← PrevPage 284 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	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