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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 901–950 of 4856 papers

TitleStatusHype
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly DetectionCode1
IM-IAD: Industrial Image Anomaly Detection Benchmark in ManufacturingCode1
LogiCode: an LLM-Driven Framework for Logical Anomaly DetectionCode1
Machine learning methods to detect money laundering in the Bitcoin blockchain in the presence of label scarcityCode1
Improving Generalizability of Graph Anomaly Detection Models via Data AugmentationCode1
Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion ModelCode1
Memory-augmented Online Video Anomaly DetectionCode1
Improving Position Encoding of Transformers for Multivariate Time Series ClassificationCode1
Unsupervised Anomaly Detection via Deep Metric Learning with End-to-End OptimizationCode1
Unsupervised Anomaly Localization with Structural Feature-AutoencodersCode1
Detecting Multivariate Time Series Anomalies with Zero Known LabelCode1
Attention-based residual autoencoder for video anomaly detectionCode1
Invariant Anomaly Detection under Distribution Shifts: A Causal PerspectiveCode1
Unsupervised Image Anomaly Detection and Segmentation Based on Pre-trained Feature MappingCode1
PANDA: Adapting Pretrained Features for Anomaly Detection and SegmentationCode1
Informative knowledge distillation for image anomaly segmentationCode1
Inpainting Transformer for Anomaly DetectionCode1
SQUID: Deep Feature In-Painting for Unsupervised Anomaly DetectionCode1
Unsupervised Traffic Accident Detection in First-Person VideosCode1
InsPLAD: A Dataset and Benchmark for Power Line Asset Inspection in UAV ImagesCode1
Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case StudyCode1
Interleaving One-Class and Weakly-Supervised Models with Adaptive Thresholding for Unsupervised Video Anomaly DetectionCode1
SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited LabelsCode1
Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device FailureCode1
An Attribute-based Method for Video Anomaly DetectionCode1
Inter-Realization Channels: Unsupervised Anomaly Detection Beyond One-Class ClassificationCode1
Localizing Anomalies via Multiscale Score Matching AnalysisCode0
Anomaly Detection: How to Artificially Increase your F1-Score with a Biased Evaluation ProtocolCode0
Locally Interpretable One-Class Anomaly Detection for Credit Card Fraud DetectionCode0
Localized Multiple Kernel Learning for Anomaly Detection: One-class ClassificationCode0
Local2Global: A distributed approach for scaling representation learning on graphsCode0
Link Analysis meets Ontologies: Are Embeddings the Answer?Code0
Lightweight Collaborative Anomaly Detection for the IoT using BlockchainCode0
LIME: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information NetworksCode0
Localizing Anomalies in Critical Infrastructure using Model-Based Drift ExplanationsCode0
Leveraging the Mahalanobis Distance to enhance Unsupervised Brain MRI Anomaly DetectionCode0
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network ApproachCode0
Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and InsightsCode0
Less-supervised learning with knowledge distillation for sperm morphology analysisCode0
Learn Suspected Anomalies from Event Prompts for Video Anomaly DetectionCode0
Leveraging Contaminated Datasets to Learn Clean-Data Distribution with Purified Generative Adversarial NetworksCode0
Leveraging Log Instructions in Log-based Anomaly DetectionCode0
Lightning Fast Video Anomaly Detection via Adversarial Knowledge DistillationCode0
Improving Time Series Encoding with Noise-Aware Self-Supervised Learning and an Efficient EncoderCode0
Anomaly Detection for Industrial Control Systems Using Sequence-to-Sequence Neural NetworksCode0
Learning Representations for Time Series ClusteringCode0
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier DetectionCode0
Learning Temporal Regularity in Video SequencesCode0
A Functional Data Perspective and Baseline On Multi-Layer Out-of-Distribution DetectionCode0
Anomaly Detection for Hybrid Butterfly Subspecies via Probability FilteringCode0
Show:102550
← PrevPage 19 of 98Next →
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