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 4111–4120 of 4856 papers

Title	Date	Tasks	Status
LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly Detection	Nov 15, 2022	Anomaly DetectionDensity Estimation	CodeCode Available
CNTS: Cooperative Network for Time Series	Feb 20, 2023	Anomaly DetectionTime Series	CodeCode Available
Real-Time Nonparametric Anomaly Detection in High-Dimensional Settings	Sep 14, 2018	Anomaly DetectionVocal Bursts Intensity Prediction	CodeCode Available
Latent Space Autoregression for Novelty Detection	Jul 4, 2018	Anomaly DetectionNovelty Detection	CodeCode Available
Long Short Term Memory Networks for Anomaly Detection in Time Series	Apr 22, 2015	Anomaly DetectionFault Detection	CodeCode Available
A real-time anomaly detection method for robots based on a flexible and sparse latent space	Apr 15, 2025	Anomaly Detection	CodeCode Available
Large Models in Dialogue for Active Perception and Anomaly Detection	Jan 27, 2025	Anomaly DetectionQuestion Answering	CodeCode Available
Anomaly Detection and Prototype Selection Using Polyhedron Curvature	Apr 5, 2020	Anomaly DetectionDenoising	CodeCode Available
Anomalous Motion Detection on Highway Using Deep Learning	Jun 15, 2020	Anomaly DetectionDeep Learning	CodeCode Available
Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning	Oct 30, 2023	Anomaly Detectionclass-incremental learning	CodeCode Available

Show:10 25 50

← PrevPage 412 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