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 2451–2500 of 4856 papers

TitleStatusHype
Rethinking Contrastive Learning in Graph Anomaly Detection: A Clean-View Perspective—0
Rethinking Metrics and Benchmarks of Video Anomaly Detection—0
Rethinking Video Anomaly Detection - A Continual Learning Approach—0
Retrieval Augmented Anomaly Detection (RAAD): Nimble Model Adjustment Without Retraining—0
Detection of Backdoors in Trained Classifiers Without Access to the Training Set—0
Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection—0
Revisited Large Language Model for Time Series Analysis through Modality Alignment—0
Revisiting DDIM Inversion for Controlling Defect Generation by Disentangling the Background—0
Revisiting randomized choices in isolation forests—0
Revitalizing Reconstruction Models for Multi-class Anomaly Detection via Class-Aware Contrastive Learning—0
ReX: A Framework for Incorporating Temporal Information in Model-Agnostic Local Explanation Techniques—0
RGI: robust GAN-inversion for mask-free image inpainting and unsupervised pixel-wise anomaly detection—0
Risk-Based Thresholding for Reliable Anomaly Detection in Concentrated Solar Power Plants—0
RLAD: Time Series Anomaly Detection through Reinforcement Learning and Active Learning—0
Road Obstacle Detection based on Unknown Objectness Scores—0
ROADS: Robust Prompt-driven Multi-Class Anomaly Detection under Domain Shift—0
A Comprehensive Guide to CAN IDS Data & Introduction of the ROAD Dataset—0
Robust and Computationally-Efficient Anomaly Detection using Powers-of-Two Networks—0
Robust and Transferable Anomaly Detection in Log Data using Pre-Trained Language Models—0
Robust Anomaly Detection and Backdoor Attack Detection Via Differential Privacy—0
Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning—0
Robust Anomaly Detection for Time-series Data—0
Robust Anomaly Detection in Images using Adversarial Autoencoders—0
Robust Anomaly Detection in Network Traffic: Evaluating Machine Learning Models on CICIDS2017—0
Robust Anomaly Detection Using Semidefinite Programming—0
Robust Attack Detection Approach for IIoT Using Ensemble Classifier—0
Robust Audio Anomaly Detection—0
Robust Distribution Alignment for Industrial Anomaly Detection under Distribution Shift—0
Robust Errant Beam Prognostics with Conditional Modeling for Particle Accelerators—0
Robust Learning of Deep Time Series Anomaly Detection Models with Contaminated Training Data—0
Robustness of ML-Enhanced IDS to Stealthy Adversaries—0
Robustness Testing of Data and Knowledge Driven Anomaly Detection in Cyber-Physical Systems—0
Robust PCA Based on Adaptive Weighted Least Squares and Low-Rank Matrix Factorization—0
Robust PCA for Anomaly Detection and Data Imputation in Seasonal Time Series—0
Robust Projection based Anomaly Extraction (RPE) in Univariate Time-Series—0
Robust Rayleigh Regression Method for SAR Image Processing in Presence of Outliers—0
Robust Semi-Supervised Anomaly Detection via Adversarially Learned Continuous Noise Corruption—0
Robust Sonar ATR Through Bayesian Pose Corrected Sparse Classification—0
Robust Spectral Filtering and Anomaly Detection—0
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks—0
Robust training on approximated minimal-entropy set—0
Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction—0
Robust Variational Autoencoder for Tabular Data with Beta Divergence—0
Robust Zero Trust Architecture: Joint Blockchain based Federated learning and Anomaly Detection based Framework—0
Rock the KASBA: Blazingly Fast and Accurate Time Series Clustering—0
RoLA: A Real-Time Online Lightweight Anomaly Detection System for Multivariate Time Series—0
Root-cause Analysis for Time-series Anomalies via Spatiotemporal Graphical Modeling in Distributed Complex Systems—0
Root Cause Analysis of Anomalies in 5G RAN Using Graph Neural Network and Transformer—0
RSM-GAN: A Convolutional Recurrent GAN for Anomaly Detection in Contaminated Seasonal Multivariate Time Series—0
RUAD: unsupervised anomaly detection in HPC systems—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