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 3661–3670 of 4856 papers

Title	Date	Tasks	Status
Lossy Compression for Robust Unsupervised Time-Series Anomaly Detection	Dec 5, 2022	Anomaly DetectionTime Series	—Unverified
Low-count Time Series Anomaly Detection	Aug 24, 2023	Anomaly DetectionTime Series	—Unverified
Low Latency Anomaly Detection and Bayesian Network Prediction of Anomaly Likelihood	Nov 11, 2016	Anomaly DetectionBIG-bench Machine Learning	—Unverified
Low-rank on Graphs plus Temporally Smooth Sparse Decomposition for Anomaly Detection in Spatiotemporal Data	Oct 23, 2020	Anomaly DetectionTensor Decomposition	—Unverified
Low-Rank Representations Meets Deep Unfolding: A Generalized and Interpretable Network for Hyperspectral Anomaly Detection	Feb 23, 2024	Anomaly Detection	—Unverified
LPC-AD: Fast and Accurate Multivariate Time Series Anomaly Detection via Latent Predictive Coding	May 5, 2022	Anomaly DetectionCloud Computing	—Unverified
LSTM-Based Anomaly Detection: Detection Rules from Extreme Value Theory	Sep 13, 2019	Anomaly DetectionPrediction	—Unverified
LSTM-based Anomaly Detection for Non-linear Dynamical System	Jun 5, 2020	Anomaly DetectionPrediction	—Unverified
LSTM for Model-Based Anomaly Detection in Cyber-Physical Systems	Oct 29, 2020	Anomaly Detection	—Unverified
Lung-DETR: Deformable Detection Transformer for Sparse Lung Nodule Anomaly Detection	Sep 8, 2024	Anomaly DetectionComputed Tomography (CT)	—Unverified

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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