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 4361–4370 of 4856 papers

Title	Date	Tasks	Status
Harnessing Collective Structure Knowledge in Data Augmentation for Graph Neural Networks	May 17, 2024	Anomaly DetectionData Augmentation	CodeCode Available
Achieving state-of-the-art performance in the Medical Out-of-Distribution (MOOD) challenge using plausible synthetic anomalies	Aug 2, 2023	Anomaly DetectionImage Segmentation	CodeCode Available
Multimodal Industrial Anomaly Detection by Crossmodal Reverse Distillation	Dec 12, 2024	Anomaly DetectionKnowledge Distillation	CodeCode Available
Hallucinated Heartbeats: Anomaly-Aware Remote Pulse Estimation	Mar 11, 2023	Anomaly DetectionFace Presentation Attack Detection	CodeCode Available
Hack Me If You Can: Aggregating AutoEncoders for Countering Persistent Access Threats Within Highly Imbalanced Data	Jun 27, 2024	Anomaly Detection	CodeCode Available
Denoising Architecture for Unsupervised Anomaly Detection in Time-Series	Aug 30, 2022	Anomaly DetectionDecoder	CodeCode Available
Anomaly Detection with Generative Adversarial Networks for Multivariate Time Series	Sep 13, 2018	Anomaly DetectionTime Series	CodeCode Available
Defending Pre-trained Language Models from Adversarial Word Substitutions Without Performance Sacrifice	May 30, 2021	Adversarial AttackAnomaly Detection	CodeCode Available
Blind Image Denoising and Inpainting Using Robust Hadamard Autoencoders	Jan 26, 2021	Anomaly DetectionDenoising	CodeCode Available
tegdet: An extensible Python Library for Anomaly Detection using Time-Evolving Graphs	Oct 17, 2022	Anomaly DetectionTime Series	CodeCode Available

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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