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 1301–1350 of 4856 papers

TitleStatusHype
Graph Fairing Convolutional Networks for Anomaly DetectionCode0
ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-Variable Context EncodingCode0
Context Enhancement with Reconstruction as Sequence for Unified Unsupervised Anomaly DetectionCode0
Anomaly Detection using One-Class Neural NetworksCode0
Graph Laplacian for Image Anomaly DetectionCode0
Anomaly Detection Using Normalizing Flow-Based Density Estimation and Synthetic Defect ClassificationCode0
Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly DetectionCode0
GradStop: Exploring Training Dynamics in Unsupervised Outlier Detection through GradientCode0
High-dimensional and Permutation Invariant Anomaly DetectionCode0
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula ProcessesCode0
Grid HTM: Hierarchical Temporal Memory for Anomaly Detection in VideosCode0
Hop-Count Based Self-Supervised Anomaly Detection on Attributed NetworksCode0
GeoTrackNet-A Maritime Anomaly Detector using Probabilistic Neural Network Representation of AIS Tracks and A Contrario DetectionCode0
Addressing the Impact of Localized Training Data in Graph Neural NetworksCode0
Generator Based Inference (GBI)Code0
Context-Aware Deep Time-Series Decomposition for Anomaly Detection in BusinessesCode0
Generative Neural Networks for Anomaly Detection in Crowded ScenesCode0
Generative Optimization Networks for Memory Efficient Data GenerationCode0
GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space ModelCode0
Human Kinematics-inspired Skeleton-based Video Anomaly DetectionCode0
Hybrid Deep Neural Networks to Infer State Models of Black-Box SystemsCode0
General Domain Adaptation Through Proportional Progressive Pseudo LabelingCode0
A MIL Approach for Anomaly Detection in Surveillance Videos from Multiple Camera ViewsCode0
Hyperedge Anomaly Detection with Hypergraph Neural NetworkCode0
gen2Out: Detecting and Ranking Generalized AnomaliesCode0
Consistency-based anomaly detection with adaptive multiple-hypotheses predictionsCode0
GDformer: Going Beyond Subsequence Isolation for Multivariate Time Series Anomaly DetectionCode0
GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly DetectionCode0
GADformer: A Transparent Transformer Model for Group Anomaly Detection on TrajectoriesCode0
Counterfactual Data Augmentation with Denoising Diffusion for Graph Anomaly DetectionCode0
Conformalized Semi-supervised Random Forest for Classification and Abnormality DetectionCode0
Anomaly Detection with Density EstimationCode0
Addressing Out-of-Label Hazard Detection in Dashcam Videos: Insights from the COOOL ChallengeCode0
Confidence-Aware and Self-Supervised Image Anomaly LocalisationCode0
Anomaly Detection using Autoencoders in High Performance Computing SystemsCode0
Fusing Dictionary Learning and Support Vector Machines for Unsupervised Anomaly DetectionCode0
GANetic Loss for Generative Adversarial Networks with a Focus on Medical ApplicationsCode0
Tensor decomposition to Compress Convolutional Layers in Deep LearningCode0
CPNet: Cross-Parallel Network for Efficient Anomaly DetectionCode0
fSEAD: a Composable FPGA-based Streaming Ensemble Anomaly Detection LibraryCode0
From Zero to Hero: Cold-Start Anomaly DetectionCode0
AD-DMKDE: Anomaly Detection through Density Matrices and Fourier FeaturesCode0
From Vision to Sound: Advancing Audio Anomaly Detection with Vision-Based AlgorithmsCode0
FT-AED: Benchmark Dataset for Early Freeway Traffic Anomalous Event DetectionCode0
Concept Drift and Anomaly Detection in Graph StreamsCode0
A Meta-Analysis of the Anomaly Detection ProblemCode0
A Multi-task Deep Learning Architecture for Maritime Surveillance using AIS Data StreamsCode0
Concentration Inequalities for Two-Sample Rank Processes with Application to Bipartite RankingCode0
From Chaos to Clarity: Time Series Anomaly Detection in Astronomical ObservationsCode0
GANomaly: Semi-Supervised Anomaly Detection via Adversarial TrainingCode0
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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
6INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
7DDADDetection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9PBASDetection AUROC99.8—Unverified
10HETMMDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4DDADDetection AUROC98.9—Unverified
5Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
6INP-Former ViT-B (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