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 4501–4510 of 4856 papers

Title	Date	Tasks	Status
Automatic Bayesian Density Analysis	Jul 24, 2018	Anomaly DetectionBayesian Inference	—Unverified
SAIFE: Unsupervised Wireless Spectrum Anomaly Detection with Interpretable Features	Jul 22, 2018	Anomaly DetectionData Compression	CodeCode Available
NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks	Jul 19, 2018	Anomaly DetectionLearning Network Representations	CodeCode Available
Anomaly Detection for Water Treatment System based on Neural Network with Automatic Architecture Optimization	Jul 19, 2018	Anomaly Detection	—Unverified
Comparison of RNN Encoder-Decoder Models for Anomaly Detection	Jul 17, 2018	Anomaly DetectionDecoder	—Unverified
Deep Generative Model using Unregularized Score for Anomaly Detection with Heterogeneous Complexity	Jul 16, 2018	Anomaly Detection	—Unverified
Are generative deep models for novelty detection truly better?	Jul 13, 2018	Anomaly DetectionNovelty Detection	CodeCode Available
Process Monitoring Using Maximum Sequence Divergence	Jul 9, 2018	Anomaly DetectionTemporal Sequences	—Unverified
Latent Space Autoregression for Novelty Detection	Jul 4, 2018	Anomaly DetectionNovelty Detection	CodeCode Available
Anomaly Detection for Skin Disease Images Using Variational Autoencoder	Jul 3, 2018	Anomaly Detection	—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