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 4101–4150 of 4856 papers

TitleStatusHype
Learning Networks from Random Walk-Based Node SimilaritiesCode0
Anomaly Detection by Recombining Gated Unsupervised ExpertsCode0
Learning Front-end Filter-bank Parameters using Convolutional Neural Networks for Abnormal Heart Sound DetectionCode0
Using Self-Supervised Learning Can Improve Model Robustness and UncertaintyCode0
Learning from Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image AnalysisCode0
TrADe Re-ID -- Live Person Re-Identification using Tracking and Anomaly DetectionCode0
Real-Time Energy Pricing in New Zealand: An Evolving Stream AnalysisCode0
Learning Deep Features for One-Class ClassificationCode0
Learning Cortical Anomaly through Masked Encoding for Unsupervised Heterogeneity MappingCode0
Dlib-ml: A Machine Learning ToolkitCode0
LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly DetectionCode0
CNTS: Cooperative Network for Time SeriesCode0
Real-Time Nonparametric Anomaly Detection in High-Dimensional SettingsCode0
Latent Space Autoregression for Novelty DetectionCode0
Long Short Term Memory Networks for Anomaly Detection in Time SeriesCode0
A real-time anomaly detection method for robots based on a flexible and sparse latent spaceCode0
Large Models in Dialogue for Active Perception and Anomaly DetectionCode0
Anomaly Detection and Prototype Selection Using Polyhedron CurvatureCode0
Anomalous Motion Detection on Highway Using Deep LearningCode0
Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental LearningCode0
Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context LearningCode0
Looking at Model Debiasing through the Lens of Anomaly DetectionCode0
A Compact Convolutional Neural Network for Textured Surface Anomaly DetectionCode0
Language-Assisted Feature Transformation for Anomaly DetectionCode0
Landmine Detection Using Autoencoders on Multi-polarization GPR Volumetric DataCode0
Real-time Safety Assessment of Dynamic Systems in Non-stationary Environments: A Review of Methods and TechniquesCode0
Known Unknowns: Uncertainty Quality in Bayesian Neural NetworksCode0
Using Visual Anomaly Detection for Task Execution MonitoringCode0
Divide and Conquer in Video Anomaly Detection: A Comprehensive Review and New ApproachCode0
Low-Latency Video Anonymization for Crowd Anomaly Detection: Privacy vs. PerformanceCode0
Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density EstimationCode0
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker DiscoveryCode0
Abnormal Event Detection in Videos using Spatiotemporal AutoencoderCode0
Dive into Time-Series Anomaly Detection: A Decade ReviewCode0
LR-IAD:Mask-Free Industrial Anomaly Detection with Logical ReasoningCode0
LSCP: Locally Selective Combination in Parallel Outlier EnsemblesCode0
Kinematic Detection of Anomalies in Human Trajectory DataCode0
A Prototype-Based Neural Network for Image Anomaly Detection and LocalizationCode0
3D unsupervised anomaly detection and localization through virtual multi-view projection and reconstruction: Clinical validation on low-dose chest computed tomographyCode0
Kernel-Based Anomaly Detection Using Generalized Hyperbolic ProcessesCode0
Reasonable Anomaly Detection in Long SequencesCode0
KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly DetectionCode0
DISYRE: Diffusion-Inspired SYnthetic REstoration for Unsupervised Anomaly DetectionCode0
M^2AD: Multi-Sensor Multi-System Anomaly Detection through Global Scoring and Calibrated ThresholdingCode0
Cluster-Wide Task Slowdown Detection in Cloud SystemCode0
Unsupervised anomaly localization in high-resolution breast scans using deep pluralistic image completionCode0
KairosAD: A SAM-Based Model for Industrial Anomaly Detection on Embedded DevicesCode0
Cloudy with a Chance of Anomalies: Dynamic Graph Neural Network for Early Detection of Cloud Services' User AnomaliesCode0
Recomposition vs. Prediction: A Novel Anomaly Detection for Discrete Events Based On AutoencoderCode0
Distributionally Robust Optimization for Deep Kernel Multiple Instance LearningCode0
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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