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 3851–3900 of 4856 papers

TitleStatusHype
P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection—0
Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device FailureCode1
Anomaly Detection-Based Unknown Face Presentation Attack DetectionCode1
ID-Conditioned Auto-Encoder for Unsupervised Anomaly Detection—0
Learning Retrospective Knowledge with Reverse Reinforcement Learning—0
Brain Tumor Anomaly Detection via Latent Regularized Adversarial Network—0
Artificial Intelligence and Machine Learning in 5G Network Security: Opportunities, advantages, and future research trends—0
Meta-Learning for One-Class Classification with Few Examples using Order-Equivariant NetworkCode0
Few-Shot One-Class Classification via Meta-LearningCode1
Deep Learning for Anomaly Detection: A Review—0
Explainable Deep One-Class ClassificationCode1
Multiple Instance-Based Video Anomaly Detection using Deep Temporal Encoding-DecodingCode0
Deep Learning Models for Visual Inspection on Automotive Assembling Line—0
Laplacian Change Point Detection for Dynamic GraphsCode1
Subject-Aware Contrastive Learning for BiosignalsCode1
Feature Extraction for Novelty Detection in Network Traffic—0
Random Partitioning Forest for Point-Wise and Collective Anomaly Detection -- Application to Intrusion DetectionCode1
Patch SVDD: Patch-level SVDD for Anomaly Detection and SegmentationCode1
Abnormal activity capture from passenger flow of elevator based on unsupervised learning and fine-grained multi-label recognition—0
Generative Damage Learning for Concrete Aging Detection using Auto-flight Images—0
Leveraging Siamese Networks for One-Shot Intrusion Detection Model—0
Efficient Deep CNN-BiLSTM Model for Network Intrusion DetectionCode1
An Investigation of Traffic Density Changes inside Wuhan during the COVID-19 Epidemic with GF-2 Time-Series Images—0
Few-Shot Anomaly Detection for Polyp Frames from ColonoscopyCode1
Anomaly Detection using Deep Reconstruction and Forecasting for Autonomous Systems—0
AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types—0
Traffic congestion anomaly detection and prediction using deep learning—0
Fixing Inventory Inaccuracies At Scale—0
Anomaly Detection in Medical Imaging with Deep Perceptual AutoencodersCode1
Locally Masked Convolution for Autoregressive ModelsCode1
A Neural Network for Determination of Latent Dimensionality in Nonnegative Matrix Factorization—0
G2D: Generate to Detect Anomaly—0
Manifolds for Unsupervised Visual Anomaly DetectionCode1
Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and FeaturesCode1
The Clever Hans Effect in Anomaly Detection—0
Deep Dense and Convolutional Autoencoders for Unsupervised Anomaly Detection in Machine Condition SoundsCode1
Use of in-the-wild images for anomaly detection in face anti-spoofing—0
Lightweight Collaborative Anomaly Detection for the IoT using BlockchainCode0
Analytical Probability Distributions and EM-Learning for Deep Generative Networks—0
Self-Supervised Representation Learning for Visual Anomaly Detection—0
A specifically designed machine learning algorithm for GNSS position time series prediction and its applications in outlier and anomaly detection and earthquake prediction—0
Plug-and-Play Anomaly Detection with Expectation Maximization Filtering—0
A Taxonomy and Review of Algorithms for Modeling and Predicting Human Driver Behavior—0
Anomalous Motion Detection on Highway Using Deep LearningCode0
Learning Latent Space Energy-Based Prior ModelCode1
Robust Variational Autoencoder for Tabular Data with Beta Divergence—0
Categorical anomaly detection in heterogeneous data using minimum description length clustering—0
Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio EstimationCode0
COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literatureCode1
Joint Training of Variational Auto-Encoder and Latent Energy-Based Model—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
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