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 571–580 of 4856 papers

Title	Date	Tasks	Status	Hype
Anomaly Detection in Aerial Videos with Transformers	Sep 25, 2022	Anomaly Detection	CodeCode Available	1
Weakly Supervised Two-Stage Training Scheme for Deep Video Fight Detection Model	Sep 23, 2022	Action RecognitionAnomaly Detection	CodeCode Available	1
Challenges in Visual Anomaly Detection for Mobile Robots	Sep 22, 2022	Anomaly Detection	CodeCode Available	1
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation	Sep 21, 2022	Anomaly DetectionData Augmentation	CodeCode Available	1
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile Robots	Sep 20, 2022	Anomaly Detection	CodeCode Available	1
An Attention-guided Multistream Feature Fusion Network for Localization of Risky Objects in Driving Videos	Sep 16, 2022	Anomaly DetectionObject	CodeCode Available	1
Deep Feature Selection for Anomaly Detection Based on Pretrained Network and Gaussian Discriminative Analysis	Sep 12, 2022	Anomaly DetectionFault Diagnosis	CodeCode Available	1
W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series Forecasting	Sep 8, 2022	Anomaly DetectionRecommendation Systems	CodeCode Available	1
Morphology-preserving Autoregressive 3D Generative Modelling of the Brain	Sep 7, 2022	AnatomyAnomaly Detection	CodeCode Available	1
HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease	Sep 5, 2022	Anomaly DetectionDiagnostic	CodeCode Available	1

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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	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