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 321–330 of 4856 papers

Title	Date	Tasks	Status	Hype
Broiler-Net: A Deep Convolutional Framework for Broiler Behavior Analysis in Poultry Houses	Jan 22, 2024	Anomaly Detection	CodeCode Available	1
Unsupervised Machine Learning for the Classification of Astrophysical X-ray Sources	Jan 22, 2024	Anomaly DetectionAstronomy	CodeCode Available	1
PHMD: An easy data access tool for prognosis and health management datasets	Jan 22, 2024	Anomaly DetectionFault Detection	CodeCode Available	1
TreeMIL: A Multi-instance Learning Framework for Time Series Anomaly Detection with Inexact Supervision	Jan 20, 2024	Anomaly DetectionTime Series	CodeCode Available	1
Towards Universal Unsupervised Anomaly Detection in Medical Imaging	Jan 19, 2024	Anomaly DetectionDiagnostic	CodeCode Available	1
PatchAD: A Lightweight Patch-based MLP-Mixer for Time Series Anomaly Detection	Jan 18, 2024	Anomaly DetectionContrastive Learning	CodeCode Available	1
Dynamic Addition of Noise in a Diffusion Model for Anomaly Detection	Jan 9, 2024	Anomaly DetectionDenoising	CodeCode Available	1
AUPIMO: Redefining Visual Anomaly Detection Benchmarks with High Speed and Low Tolerance	Jan 3, 2024	Anomaly Detection	CodeCode Available	1
Soft Contrastive Learning for Time Series	Dec 27, 2023	Anomaly DetectionContrastive Learning	CodeCode Available	1
TimesURL: Self-supervised Contrastive Learning for Universal Time Series Representation Learning	Dec 25, 2023	Anomaly DetectionContrastive Learning	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