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 1551–1575 of 4856 papers

Title	Date	Tasks	Status	Hype
Guarding the Grid: Enhancing Resilience in Automated Residential Demand Response Against False Data Injection Attacks	Dec 14, 2023	Anomaly DetectionDecision Making	—Unverified	0
An Incremental Unified Framework for Small Defect Inspection	Dec 14, 2023	Anomaly Detectioncontinual anomaly detection	CodeCode Available	1
Towards Efficient Quantum Anomaly Detection: One-Class SVMs using Variable Subsampling and Randomized Measurements	Dec 14, 2023	Anomaly Detection	CodeCode Available	0
Efficient Representation of the Activation Space in Deep Neural Networks	Dec 13, 2023	Anomaly Detectionspeech-recognition	—Unverified	0
GenDet: Towards Good Generalizations for AI-Generated Image Detection	Dec 12, 2023	Anomaly Detection	CodeCode Available	2
How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation	Dec 12, 2023	Anomaly DetectionAutonomous Driving	CodeCode Available	1
Meta-survey on outlier and anomaly detection	Dec 12, 2023	Anomaly DetectionBenchmarking	CodeCode Available	0
Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection	Dec 12, 2023	Anomaly DetectionGPU	—Unverified	0
QuickQuakeBuildings: Post-earthquake SAR-Optical Dataset for Quick Damaged-building Detection	Dec 11, 2023	Anomaly DetectionDamaged Building Detection	CodeCode Available	1
DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection	Dec 11, 2023	Anomaly DetectionDenoising	CodeCode Available	2
Detecting Contextual Network Anomalies with Graph Neural Networks	Dec 11, 2023	Anomaly DetectionContextual Anomaly Detection	—Unverified	0
Unsupervised KPIs-Based Clustering of Jobs in HPC Data Centers	Dec 11, 2023	Anomaly DetectionClustering	—Unverified	0
Reinforcement Neighborhood Selection for Unsupervised Graph Anomaly Detection	Dec 9, 2023	Anomaly DetectionGraph Anomaly Detection	—Unverified	0
Physics-Informed Convolutional Autoencoder for Cyber Anomaly Detection in Power Distribution Grids	Dec 8, 2023	Anomaly Detection	—Unverified	0
Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning	Dec 7, 2023	Anomaly Detection	—Unverified	0
Adversarial Denoising Diffusion Model for Unsupervised Anomaly Detection	Dec 7, 2023	Anomaly DetectionDenoising	—Unverified	0
An unsupervised approach towards promptable defect segmentation in laser-based additive manufacturing by Segment Anything	Dec 7, 2023	Anomaly DetectionAstronomy	—Unverified	0
Detection and Imputation based Two-Stage Denoising Diffusion Power System Measurement Recovery under Cyber-Physical Uncertainties	Dec 7, 2023	Anomaly DetectionDenoising	—Unverified	0
Data-Driven Semi-Supervised Machine Learning with Safety Indicators for Abnormal Driving Behavior Detection	Dec 7, 2023	Anomaly Detection	—Unverified	0
Multimodal Industrial Anomaly Detection by Crossmodal Feature Mapping	Dec 7, 2023	Anomaly Detection	CodeCode Available	1
A brief introduction to a framework named Multilevel Guidance-Exploration Network	Dec 7, 2023	Anomaly Detection	CodeCode Available	0
Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs	Dec 7, 2023	AnatomyAnomaly Detection	CodeCode Available	1
How Low Can You Go? Surfacing Prototypical In-Distribution Samples for Unsupervised Anomaly Detection	Dec 6, 2023	Anomaly DetectionDefect Detection	—Unverified	0
Anomaly Detection for Scalable Task Grouping in Reinforcement Learning-based RAN Optimization	Dec 6, 2023	Anomaly Detection	—Unverified	0
Pseudo Replay-based Class Continual Learning for Online New Category Anomaly Detection in Advanced Manufacturing	Dec 5, 2023	Anomaly Detectionclass-incremental learning	—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	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