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 771–780 of 4856 papers

Title	Date	Tasks	Status	Hype
Few-shot Network Anomaly Detection via Cross-network Meta-learning	Feb 22, 2021	Anomaly DetectionFew-Shot Learning	CodeCode Available	1
Negative Data Augmentation	Feb 9, 2021	Action RecognitionAnomaly Detection	CodeCode Available	1
Clustered Hierarchical Anomaly and Outlier Detection Algorithms	Feb 9, 2021	Anomaly DetectionClustering	CodeCode Available	1
[Re] Learning Memory Guided Normality for Anomaly Detection	Jan 29, 2021	Anomaly DetectionHyperparameter Optimization	CodeCode Available	1
Deep One-Class Classification via Interpolated Gaussian Descriptor	Jan 25, 2021	Anomaly DetectionClassification	CodeCode Available	1
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning	Jan 25, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1
Iterative weak/self-supervised classification framework for abnormal events detection	Jan 3, 2021	Abnormal Event Detection In VideoAnomaly Detection	CodeCode Available	1
DRAEM - A Discriminatively Trained Reconstruction Embedding for Surface Anomaly Detection	Jan 1, 2021	Anomaly DetectionAnomaly Localization	CodeCode Available	1
Unsupervised Anomaly Detection by Robust Collaborative Autoencoders	Jan 1, 2021	Anomaly DetectionMissing Values	CodeCode Available	1
Road Anomaly Detection by Partial Image Reconstruction With Segmentation Coupling	Jan 1, 2021	Anomaly DetectionAutonomous Driving	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	HETMM	Detection AUROC	99.8	—	Unverified
7	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	PBAS	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	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	DDAD	Detection AUROC	98.9	—	Unverified
6	Dinomaly ViT-L (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