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 3051–3060 of 4856 papers

Title	Date	Tasks	Status	Hype
Scalable and Decentralized Algorithms for Anomaly Detection via Learning-Based Controlled Sensing	Dec 8, 2021	Anomaly DetectionDecision Making	—Unverified	0
Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection	Dec 7, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	CodeCode Available	1
Online false discovery rate control for anomaly detection in time series	Dec 6, 2021	Anomaly DetectionTime Series	—Unverified	0
Smart Metering System Capable of Anomaly Detection by Bi-directional LSTM Autoencoder	Dec 6, 2021	Anomaly DetectionEvent Detection	—Unverified	0
Autoencoders for Semivisible Jet Detection	Dec 6, 2021	Anomaly Detection	—Unverified	0
Anomaly Detection in IR Images of PV Modules using Supervised Contrastive Learning	Dec 6, 2021	Anomaly DetectionContrastive Learning	CodeCode Available	1
Anomaly Detection of Wind Turbine Time Series using Variational Recurrent Autoencoders	Dec 5, 2021	Anomaly DetectionTime Series	CodeCode Available	1
Constrained Adaptive Projection with Pretrained Features for Anomaly Detection	Dec 5, 2021	Anomaly Detection	CodeCode Available	0
Automatic deforestation detectors based on frequentist statistics and their extensions for other spatial objects	Dec 2, 2021	Anomaly Detection	CodeCode Available	0
SCNet: A Generalized Attention-based Model for Crack Fault Segmentation	Dec 2, 2021	Anomaly DetectionAnomaly Segmentation	—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