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 3611–3620 of 4856 papers

Title	Date	Tasks	Status	Hype
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs	Dec 23, 2020	Anomaly DetectionArticles	CodeCode Available	1
Identification of Unexpected Decisions in Partially Observable Monte-Carlo Planning: a Rule-Based Approach	Dec 23, 2020	Anomaly DetectionRobot Navigation	CodeCode Available	0
General Domain Adaptation Through Proportional Progressive Pseudo Labeling	Dec 23, 2020	Anomaly DetectionDomain Adaptation	CodeCode Available	0
Dual-encoder Bidirectional Generative Adversarial Networks for Anomaly Detection	Dec 22, 2020	Anomaly Detection	—Unverified	0
Unsupervised in-distribution anomaly detection of new physics through conditional density estimation	Dec 21, 2020	Anomaly DetectionDensity Estimation	—Unverified	0
Improving unsupervised anomaly localization by applying multi-scale memories to autoencoders	Dec 21, 2020	Anomaly DetectionAnomaly Localization	—Unverified	0
Unsupervised Anomaly Detectors to Detect Intrusions in the Current Threat Landscape	Dec 21, 2020	Anomaly DetectionBinary Classification	—Unverified	0
Computer-aided abnormality detection in chest radiographs in a clinical setting via domain-adaptation	Dec 19, 2020	Anomaly DetectionDomain Adaptation	—Unverified	0
Image-Based Jet Analysis	Dec 17, 2020	Anomaly DetectionGeneral Classification	—Unverified	0
Anomaly Detection and Localization based on Double Kernelized Scoring and Matrix Kernels	Dec 15, 2020	Anomaly DetectionTime Series Analysis	—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