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 801–850 of 4856 papers

TitleStatusHype
Laplacian Change Point Detection for Single and Multi-view Dynamic GraphsCode1
A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection AlgorithmsCode1
Set Features for Anomaly DetectionCode1
FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language ModelCode1
Fake It Till You Make It: Towards Accurate Near-Distribution Novelty DetectionCode1
FAIR: Frequency-aware Image Restoration for Industrial Visual Anomaly DetectionCode1
FAPM: Fast Adaptive Patch Memory for Real-time Industrial Anomaly DetectionCode1
Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution DetectionCode1
A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open ChallengesCode1
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged ApproachCode1
Learning Generalized Spoof Cues for Face Anti-spoofingCode1
Are we certain it's anomalous?Code1
FastAno: Fast Anomaly Detection via Spatio-temporal Patch TransformationCode1
A Body Part Embedding Model With Datasets for Measuring 2D Human Motion SimilarityCode1
An Attribute-based Method for Video Anomaly DetectionCode1
FastLogAD: Log Anomaly Detection with Mask-Guided Pseudo Anomaly Generation and DiscriminationCode1
SliceNStitch: Continuous CP Decomposition of Sparse Tensor StreamsCode1
Fast Unsupervised Anomaly Detection in Traffic VideosCode1
A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly DetectionCode1
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data DetectionCode1
A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor DetectionCode1
Federated Foundation Models on Heterogeneous Time SeriesCode1
AnoDFDNet: A Deep Feature Difference Network for Anomaly DetectionCode1
Federated PCA on Grassmann Manifold for Anomaly Detection in IoT NetworksCode1
Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly DetectionCode1
A SAM-guided Two-stream Lightweight Model for Anomaly DetectionCode1
Inter-Realization Channels: Unsupervised Anomaly Detection Beyond One-Class ClassificationCode1
Attention-based residual autoencoder for video anomaly detectionCode1
Few-shot Network Anomaly Detection via Cross-network Meta-learningCode1
Few-Shot One-Class Classification via Meta-LearningCode1
Intrinsic persistent homology via density-based metric learningCode1
Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case StudyCode1
Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural NetworksCode1
Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly DetectionCode1
First-shot anomaly sound detection for machine condition monitoring: A domain generalization baselineCode1
Learning a Cross-modality Anomaly Detector for Remote Sensing ImageryCode1
Invariant Anomaly Detection under Distribution Shifts: A Causal PerspectiveCode1
Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly DetectionCode1
FrAug: Frequency Domain Augmentation for Time Series ForecastingCode1
FUN-AD: Fully Unsupervised Learning for Anomaly Detection with Noisy Training DataCode1
FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series ClassificationCode1
Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly DetectionCode1
IPMix: Label-Preserving Data Augmentation Method for Training Robust ClassifiersCode1
Fully Convolutional Cross-Scale-Flows for Image-based Defect DetectionCode1
StRegA: Unsupervised Anomaly Detection in Brain MRIs using a Compact Context-encoding Variational AutoencoderCode1
F-SE-LSTM: A Time Series Anomaly Detection Method with Frequency Domain InformationCode1
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization ApproachCode1
Future Frame Prediction for Anomaly Detection – A New BaselineCode1
Future Frame Prediction for Anomaly Detection -- A New BaselineCode1
Asymmetric Student-Teacher Networks for Industrial Anomaly DetectionCode1
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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