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 2151–2200 of 4856 papers

TitleStatusHype
GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud DetectionCode1
Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation—0
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection—0
Unsupervised Anomaly Detection with Local-Sensitive VQVAE and Global-Sensitive Transformers—0
Searching for long faint astronomical high energy transients: a data driven approachCode1
Attention Boosted Autoencoder for Building Energy Anomaly Detection—0
Hard-normal Example-aware Template Mutual Matching for Industrial Anomaly DetectionCode1
Disruption Precursor Onset Time Study Based on Semi-supervised Anomaly Detection—0
SimpleNet: A Simple Network for Image Anomaly Detection and LocalizationCode2
WinCLIP: Zero-/Few-Shot Anomaly Classification and SegmentationCode2
Topological Pooling on GraphsCode0
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level LatenciesCode2
Interpretable Anomaly Detection via Discrete Optimization—0
Anomaly Detection under Distribution ShiftCode1
Failure-tolerant Distributed Learning for Anomaly Detection in Wireless Networks—0
Hierarchical Semantic Contrast for Scene-aware Video Anomaly Detection—0
Confidence-Aware and Self-Supervised Image Anomaly LocalisationCode0
Complementary Pseudo Multimodal Feature for Point Cloud Anomaly DetectionCode1
TSI-GAN: Unsupervised Time Series Anomaly Detection using Convolutional Cycle-Consistent Generative Adversarial NetworksCode1
One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship LearningCode1
Unbiased Multiple Instance Learning for Weakly Supervised Video Anomaly DetectionCode1
Anomaly Detection in Aeronautics Data with Quantum-compatible Discrete Deep Generative Model—0
A Novel Multi-Stage Approach for Hierarchical Intrusion DetectionCode0
Dens-PU: PU Learning with Density-Based Positive Labeled Augmentation—0
Defect Detection Approaches Based on Simulated Reference Image—0
Unlocking Layer-wise Relevance Propagation for Autoencoders—0
Focus or Not: A Baseline for Anomaly Event Detection On the Open Public Places with Satellite ImagesCode0
Did You Train on My Dataset? Towards Public Dataset Protection with Clean-Label Backdoor WatermarkingCode0
PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomalies—0
GADformer: A Transparent Transformer Model for Group Anomaly Detection on TrajectoriesCode0
A Bi-LSTM Autoencoder Framework for Anomaly Detection -- A Case Study of a Wind Power Dataset—0
Wireless Sensor Networks anomaly detection using Machine Learning: A Survey—0
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection—0
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly DetectionCode2
Towards Phytoplankton Parasite Detection Using AutoencodersCode0
Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and InsightsCode0
Network Anomaly Detection Using Federated Learning—0
Spacecraft Anomaly Detection with Attention Temporal Convolution NetworkCode1
Hallucinated Heartbeats: Anomaly-Aware Remote Pulse EstimationCode0
Interpretable Outlier Summarization—0
Anomaly Detection with Ensemble of Encoder and Decoder—0
3D Masked Autoencoders with Application to Anomaly Detection in Non-Contrast Enhanced Breast MRI—0
Learning Global-Local Correspondence with Semantic Bottleneck for Logical Anomaly Detection—0
Deep Anomaly Detection on Tennessee Eastman Process Data—0
Adapting Contrastive Language-Image Pretrained (CLIP) Models for Out-of-Distribution DetectionCode0
Automated visual inspection of CMS HGCAL silicon sensor surface using an ensemble of a deep convolutional autoencoder and classifier—0
Multi-level Memory-augmented Appearance-Motion Correspondence Framework for Video Anomaly Detection—0
Diversity-Measurable Anomaly DetectionCode1
Updated version: A Video Anomaly Detection Framework based on Appearance-Motion Semantics Representation Consistency—0
Learning Representation for Anomaly Detection of Vehicle Trajectories—0
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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