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 1551–1560 of 4856 papers

Title	Date	Tasks	Status
DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive Learning Reconstruction	Dec 21, 2024	Anomaly DetectionContrastive Learning	—Unverified
An Asymmetric Loss with Anomaly Detection LSTM Framework for Power Consumption Prediction	Feb 5, 2023	Anomaly DetectionLoad Forecasting	—Unverified
AAD: Adaptive Anomaly Detection through traffic surveillance videos	Aug 29, 2018	Action DetectionActivity Detection	—Unverified
Demo: A Digital Twin of the 5G Radio Access Network for Anomaly Detection Functionality	Aug 30, 2023	Anomaly Detection	—Unverified
Does Your Phone Know Your Touch?	Sep 10, 2018	Anomaly DetectionPosition	—Unverified
DCFormer: Efficient 3D Vision-Language Modeling with Decomposed Convolutions	Feb 7, 2025	Anomaly DetectionImage-text Retrieval	—Unverified
Anomaly Subsequence Detection with Dynamic Local Density for Time Series	Jun 28, 2019	Anomaly DetectionDensity Estimation	—Unverified
An Anomaly Detection System Based on Generative Classifiers for Controller Area Network	Dec 28, 2024	Anomaly DetectionBayesian Inference	—Unverified
Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative Data	Dec 23, 2021	Anomaly DetectionOut-of-Distribution Detection	—Unverified
An Anomaly Detection Method for Satellites Using Monte Carlo Dropout	Nov 27, 2022	Anomaly DetectionTime Series	—Unverified

Show:10 25 50

← PrevPage 156 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	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