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 4431–4440 of 4856 papers

Title	Date	Tasks	Status
SAM-kNN Regressor for Online Learning in Water Distribution Networks	Apr 4, 2022	Anomaly Detection	CodeCode Available
Generator Based Inference (GBI)	May 30, 2025	Anomaly Detectionparameter estimation	CodeCode Available
Uncertainty on Asynchronous Time Event Prediction	Nov 13, 2019	Anomaly DetectionPrediction	CodeCode Available
Generative Optimization Networks for Memory Efficient Data Generation	Oct 6, 2021	Anomaly DetectionTime Series	CodeCode Available
NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks	Jul 19, 2018	Anomaly DetectionLearning Network Representations	CodeCode Available
Uncertainty Quantification in Anomaly Detection with Cross-Conformal p-Values	Feb 26, 2024	Anomaly DetectionConformal Prediction	CodeCode Available
BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly Detection	Jun 18, 2021	Anomaly DetectionCombinatorial Optimization	CodeCode Available
Anomaly detection using prediction error with Spatio-Temporal Convolutional LSTM	May 18, 2022	Anomaly DetectionPrediction	CodeCode Available
Unsupervised Learning of Anomaly Detection from Contaminated Image Data using Simultaneous Encoder Training	May 27, 2019	Anomaly Detectionvalid	CodeCode Available
BiGSeT: Binary Mask-Guided Separation Training for DNN-based Hyperspectral Anomaly Detection	Jul 14, 2023	Anomaly Detection	CodeCode Available

Show:10 25 50

← PrevPage 444 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