SOTAVerified

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

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Showing 3701–3725 of 4856 papers

TitleStatusHype
MadSGM: Multivariate Anomaly Detection with Score-based Generative Models—0
MAEDiff: Masked Autoencoder-enhanced Diffusion Models for Unsupervised Anomaly Detection in Brain Images—0
OrionBench: Benchmarking Time Series Generative Models in the Service of the End-User—0
MAMBO: High-Resolution Generative Approach for Mammography Images—0
MANTA: A Large-Scale Multi-View and Visual-Text Anomaly Detection Dataset for Tiny Objects—0
Autoencoder-Based Visual Anomaly Localization for Manufacturing Quality Control—0
Markus Thill Temporal convolutional autoencoder for unsupervised anomaly detection in time series—0
MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery—0
Masked Transformer for image Anomaly Localization—0
Master-Auxiliary: an efficient aggregation strategy for video anomaly detection—0
MathPhys-Guided Coarse-to-Fine Anomaly Synthesis with SQE-Driven Bi-Level Optimization for Anomaly Detection—0
Matrix Profile based Anomaly Detection in Streaming Gait Data for Fall Prevention—0
Matrix Profile for Anomaly Detection on Multidimensional Time Series—0
Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series—0
MAUCell: An Adaptive Multi-Attention Framework for Video Frame Prediction—0
Maximally Divergent Intervals for Anomaly Detection—0
MC3D-AD: A Unified Geometry-aware Reconstruction Model for Multi-category 3D Anomaly Detection—0
MCM-aware Twin-least-square GAN for Hyperspectral Anomaly Detection—0
MDGAN: Boosting Anomaly Detection Using \ -Discriminator Generative Adversarial Networks—0
Measuring sentence parallelism using Mahalanobis distances: The NRC unsupervised submissions to the WMT18 Parallel Corpus Filtering shared task—0
MEDAVET: Traffic Vehicle Anomaly Detection Mechanism based on spatial and temporal structures in vehicle traffic—0
MedDiff-FM: A Diffusion-based Foundation Model for Versatile Medical Image Applications—0
Median of Forests for Robust Density Estimation—0
Medical Image Analysis using Convolutional Neural Networks: A Review—0
MeLIAD: Interpretable Few-Shot Anomaly Detection with Metric Learning and Entropy-based Scoring—0
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All datasetsMVTec ADVisAMVTec LOCO ADOne-class CIFAR-10CUHK AvenueShanghaiTechFishyscapes L&FUCR Anomaly ArchiveMPDDBTADOne-class CIFAR-100UBnormal

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016—Unverified
2CPR-fast(TensorRT)FPS362—Unverified
3CPR(TensorRT)FPS130—Unverified
4GLASSDetection AUROC99.9—Unverified
5UniNetDetection AUROC99.9—Unverified
6HETMMDetection AUROC99.8—Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9DDADDetection AUROC99.8—Unverified
10PBASDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
5DDADDetection AUROC98.9—Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
7DiffusionADDetection AUROC98.8—Unverified
8GLASSDetection AUROC98.8—Unverified
9TransFusionDetection AUROC98.7—Unverified
10HETMMDetection AUROC98.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3—Unverified
2PSADAvg. Detection AUROC94.9—Unverified