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 3301–3350 of 4856 papers

TitleStatusHype
A Method for Detecting Abnormal Data of Network Nodes Based on Convolutional Neural Network—0
Approximate Maximum Halfspace Discrepancy—0
Task-agnostic Continual Learning with Hybrid Probabilistic Models—0
Generalized One-Class Learning Using Pairs of Complementary Classifiers—0
Innovations Autoencoder and its Application in One-class Anomalous Sequence Detection—0
A new Video Synopsis Based Approach Using Stereo Camera—0
Detecting Anomalous User Behavior in Remote Patient Monitoring—0
Skeleton-based human action evaluation using graph convolutional network for monitoring Alzheimer’s progression—0
Affine-Invariant Integrated Rank-Weighted Depth: Definition, Properties and Finite Sample Analysis—0
Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time SeriesCode0
Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density EstimationCode0
Large-Scale Network Embedding in Apache Spark—0
Glancing at the Patch: Anomaly Localization With Global and Local Feature Comparison—0
Deep Learning in Latent Space for Video Prediction and CompressionCode1
TS2Vec: Towards Universal Representation of Time SeriesCode1
BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly DetectionCode0
Anomaly Detection in Dynamic Graphs via TransformerCode1
Anomaly Detection and Automated Labeling for Voter Registration File Changes—0
Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions—0
Anomaly Detection in Video Sequences: A Benchmark and Computational ModelCode1
X-MAN: Explaining multiple sources of anomalies in video—0
FastAno: Fast Anomaly Detection via Spatio-temporal Patch TransformationCode1
Towards Total Recall in Industrial Anomaly DetectionCode2
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data DetectionCode1
Multivariate Business Process Representation Learning utilizing Gramian Angular Fields and Convolutional Neural Networks—0
Time Series Anomaly Detection for Cyber-Physical Systems via Neural System Identification and Bayesian FilteringCode1
MLPerf Tiny BenchmarkCode1
A Comprehensive Survey on Graph Anomaly Detection with Deep LearningCode1
Inverting Adversarially Robust Networks for Image SynthesisCode0
RadArnomaly: Protecting Radar Systems from Data Manipulation Attacks—0
Graph Neural Network-Based Anomaly Detection in Multivariate Time SeriesCode1
Time Series Anomaly Detection with label-free Model Selection—0
Unsupervised Anomaly Detection Ensembles using Item Response TheoryCode0
HIFI: Anomaly Detection for Multivariate Time Series with High-order Feature Interactions—0
Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection—0
From Unsupervised to Semi-supervised Anomaly Detection Methods for HRRP Targets—0
GBHT: Gradient Boosting Histogram Transform for Density Estimation—0
Predicting Next Local Appearance for Video Anomaly DetectionCode0
Spot the Difference: Detection of Topological Changes via Geometric AlignmentCode0
DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly DetectionCode1
XBNet : An Extremely Boosted Neural NetworkCode1
Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory TracingCode0
Implicit field learning for unsupervised anomaly detection in medical imagesCode1
Towards Deep Industrial Transfer Learning for Anomaly Detection on Time Series Data—0
Deep Random Projection Outlyingness for Unsupervised Anomaly Detection—0
Sketch-Based Anomaly Detection in Streaming GraphsCode1
Shifting Transformation Learning for Out-of-Distribution Detection—0
Mean-Shifted Contrastive Loss for Anomaly DetectionCode1
MemStream: Memory-Based Streaming Anomaly DetectionCode1
FlexParser -- the adaptive log file parser for continuous results in a changing world—0
Show:102550
← PrevPage 67 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