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 4551–4600 of 4856 papers

TitleStatusHype
Unsupervised Network Anomaly Detection with Autoencoders and Traffic ImagesCode0
FDM-Bench: A Comprehensive Benchmark for Evaluating Large Language Models in Additive Manufacturing TasksCode0
Fast Particle-based Anomaly Detection Algorithm with Variational AutoencoderCode0
On Generalization of Graph Autoencoders with Adversarial TrainingCode0
Time and Cost-Efficient Bathymetric Mapping System using Sparse Point Cloud Generation and Automatic Object DetectionCode0
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and ApplicationsCode0
Unfooling Perturbation-Based Post Hoc ExplainersCode0
Online Adaptive Asymmetric Active Learning with Limited BudgetsCode0
Automatic deforestation detectors based on frequentist statistics and their extensions for other spatial objectsCode0
Fast Adaptive RNN Encoder-Decoder for Anomaly Detection in SMD Assembly MachineCode0
A brief introduction to a framework named Multilevel Guidance-Exploration NetworkCode0
Online anomaly detection using statistical leverage for streaming business process eventsCode0
Deep Anomaly Detection under Labeling Budget ConstraintsCode0
Decoupled Appearance and Motion Learning for Efficient Anomaly Detection in Surveillance VideoCode0
Video Anomaly Detection by Estimating Likelihood of RepresentationsCode0
Online-compatible Unsupervised Non-resonant Anomaly DetectionCode0
Online Cyber-Attack Detection in Smart Grid: A Reinforcement Learning ApproachCode0
A MIL Approach for Anomaly Detection in Surveillance Videos from Multiple Camera ViewsCode0
Self-supervised Representation Learning for Reliable Robotic Monitoring of Fruit AnomaliesCode0
AdeNet: Deep learning architecture that identifies damaged electrical insulators in power linesCode0
f-AnoGAN: Fast Unsupervised Anomaly Detection with Generative Adversarial NetworksCode0
FANFOLD: Graph Normalizing Flows-driven Asymmetric Network for Unsupervised Graph-Level Anomaly DetectionCode0
DConAD: A Differencing-based Contrastive Representation Learning Framework for Time Series Anomaly DetectionCode0
DCAD-2000: A Multilingual Dataset across 2000+ Languages with Data Cleaning as Anomaly DetectionCode0
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed GraphsCode0
Dimensionless Anomaly Detection on Multivariate Streams with Variance Norm and Path SignatureCode0
Benchmarking Jetson Edge Devices with an End-to-end Video-based Anomaly Detection SystemCode0
Online Self-Evolving Anomaly Detection in Cloud Computing EnvironmentsCode0
Self-Supervised Transformer-based Contrastive Learning for Intrusion Detection SystemsCode0
Anomaly Detection on Financial Time Series by Principal Component Analysis and Neural NetworksCode0
Online Topology Identification from Vector Autoregressive Time SeriesCode0
DAD++: Improved Data-free Test Time Adversarial DefenseCode0
Self-supervised vision-langage alignment of deep learning representations for bone X-rays analysisCode0
Deep State Inference: Toward Behavioral Model Inference of Black-box Software SystemsCode0
On Periodicity Detection and Structural Periodic SimilarityCode0
Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-raysCode0
Unsupervised real-time anomaly detection for streaming dataCode0
Bayesian Nonparametric Submodular Video Partition for Robust Anomaly DetectionCode0
Anomaly Detection of Adversarial Examples using Class-conditional Generative Adversarial NetworksCode0
on the effectiveness of generative adversarial network on anomaly detectionCode0
FADE: Forecasting for Anomaly Detection on ECGCode0
Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral imagesCode0
Semantic Novelty Detection in Natural Language DescriptionsCode0
A Classifier-Based Approach to Multi-Class Anomaly Detection for Astronomical TransientsCode0
Semi-automatic staging area for high-quality structured data extraction from scientific literatureCode0
Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent EmbeddingsCode0
DABL: Detecting Semantic Anomalies in Business Processes Using Large Language ModelsCode0
Backdoor Attack against One-Class Sequential Anomaly Detection ModelsCode0
(1 + )-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data SetsCode0
On the True Distribution Approximation of Minimum Bayes-Risk DecodingCode0
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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