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 2781–2790 of 4856 papers

Title	Date	Tasks	Status	Hype
Anomaly detection using prediction error with Spatio-Temporal Convolutional LSTM	May 18, 2022	Anomaly DetectionPrediction	CodeCode Available	0
Automating In-Network Machine Learning	May 18, 2022	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available	1
Unsupervised Features Ranking via Coalitional Game Theory for Categorical Data	May 17, 2022	Anomaly DetectionFeature Importance	CodeCode Available	0
Federated Anomaly Detection over Distributed Data Streams	May 16, 2022	Anomaly DetectionFederated Learning	—Unverified	0
Unsupervised Abnormal Traffic Detection through Topological Flow Analysis	May 14, 2022	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified	0
Self-Supervised Masking for Unsupervised Anomaly Detection and Localization	May 13, 2022	Anomaly DetectionAnomaly Localization	—Unverified	0
Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review	May 13, 2022	Anomaly Detectioncompressed sensing	—Unverified	0
A Vision Inspired Neural Network for Unsupervised Anomaly Detection in Unordered Data	May 13, 2022	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified	0
Deep Learning for Prawn Farming: Forecasting and Anomaly Detection	May 12, 2022	Anomaly DetectionDeep Learning	—Unverified	0
Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks	May 10, 2022	Anomaly DetectionAttribute	—Unverified	0

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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