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 3821–3830 of 4856 papers

Title	Date	Tasks	Status	Hype
Neural Batch Sampling with Reinforcement Learning for Semi-Supervised Anomaly Detection	Aug 1, 2020	Anomaly Detectionreinforcement-learning	—Unverified	0
Clustering Driven Deep Autoencoder for Video Anomaly Detection	Aug 1, 2020	Anomaly DetectionClustering	—Unverified	0
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models	Jul 30, 2020	Anomaly DetectionTime Series	—Unverified	0
On the Nature and Types of Anomalies: A Review of Deviations in Data	Jul 30, 2020	Anomaly Detection	—Unverified	0
A General Framework For Detecting Anomalous Inputs to DNN Classifiers	Jul 29, 2020	Anomaly Detectionimage-classification	CodeCode Available	1
Fast Unsupervised Anomaly Detection in Traffic Videos	Jul 28, 2020	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	1
Cassandra: Detecting Trojaned Networks from Adversarial Perturbations	Jul 28, 2020	Adversarial DefenseAnomaly Detection	—Unverified	0
A Deep Learning Framework for Generation and Analysis of Driving Scenario Trajectories	Jul 28, 2020	Anomaly DetectionAutonomous Driving	—Unverified	0
Anomaly detection in Context-aware Feature Models	Jul 28, 2020	Anomaly Detection	—Unverified	0
DeScarGAN: Disease-Specific Anomaly Detection with Weak Supervision	Jul 28, 2020	Anomaly Detection	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	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