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 2701–2750 of 4856 papers

TitleStatusHype
Study of the Impact of the Big Data Era on Accounting and Auditing—0
Sub-clusters of Normal Data for Anomaly Detection—0
Subgraph2vec: A random walk-based algorithm for embedding knowledge graphs—0
Subset Multivariate Collective And Point Anomaly Detection—0
Subspace Modeling for Fast Out-Of-Distribution and Anomaly Detection—0
Successive Convex Approximation Algorithms for Sparse Signal Estimation with Nonconvex Regularizations—0
Successive Data Injection in Conditional Quantum GAN Applied to Time Series Anomaly Detection—0
SunDown: Model-driven Per-Panel Solar Anomaly Detection for Residential Arrays—0
SuperAD: A Training-free Anomaly Classification and Segmentation Method for CVPR 2025 VAND 3.0 Workshop Challenge Track 1: Adapt & Detect—0
Supervised Anomaly Detection based on Deep Autoregressive Density Estimators—0
Supervised Anomaly Detection in Uncertain Pseudoperiodic Data Streams—0
Supervised Anomaly Detection Method Combining Generative Adversarial Networks and Three-Dimensional Data in Vehicle Inspections—0
Supervised Time Series Classification for Anomaly Detection in Subsea Engineering—0
Support Vector Based Anomaly Detection in Federated Learning—0
Surface abnormality detection in medical and inspection systems using energy variations in co-occurrence matrixes—0
Surprisal Driven k-NN for Robust and Interpretable Nonparametric Learning—0
Survey on video anomaly detection in dynamic scenes with moving cameras—0
Suspicious and Anomaly Detection—0
SymED: Adaptive and Online Symbolic Representation of Data on the Edge—0
Synchronized Stepwise Control of Firing and Learning Thresholds in a Spiking Randomly Connected Neural Network toward Hardware Implementation—0
Synchrophasor Data Anomaly Detection on Grid Edge by 5G Communication and Adjacent Compute—0
Syntactic sensitive complexity for symbol-free sequence—0
Synthetic Aperture Anomaly Imaging—0
Synthetic outlier generation for anomaly detection in autonomous driving—0
Synthetic Pseudo Anomalies for Unsupervised Video Anomaly Detection: A Simple yet Efficient Framework based on Masked Autoencoder—0
Synthetic User Behavior Sequence Generation with Large Language Models for Smart Homes—0
Systematic Review: Anomaly Detection in Connected and Autonomous Vehicles—0
System Calls for Malware Detection and Classification: Methodologies and Applications—0
TAAD: Time-varying adversarial anomaly detection in dynamic graphs—0
TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models—0
TAB: Text-Align Anomaly Backbone Model for Industrial Inspection Tasks—0
Tackling Diverse Minorities in Imbalanced Classification—0
TAD-Bench: A Comprehensive Benchmark for Embedding-Based Text Anomaly Detection—0
TADPOLE: Task ADapted Pre-Training via AnOmaLy DEtection—0
TAGA: Self-supervised Learning for Template-free Animatable Gaussian Articulated Model—0
Tail of Distribution GAN (TailGAN): Generative-Adversarial-Network-Based Boundary Formation—0
Tailoring Machine Learning for Process Mining—0
Taming Anomalies with Down-Up Sampling Networks: Group Center Preserving Reconstruction for 3D Anomaly Detection—0
Targeted collapse regularized autoencoder for anomaly detection: black hole at the center—0
Task Agnostic and Post-hoc Unseen Distribution Detection—0
Task-agnostic Continual Learning with Hybrid Probabilistic Models—0
Task-aware Similarity Learning for Event-triggered Time Series—0
Task-Oriented Connectivity for Networked Robotics with Generative AI and Semantic Communications—0
Task-Oriented Optimal Sequencing of Visualization Charts—0
TauAD: MRI-free Tau Anomaly Detection in PET Imaging via Conditioned Diffusion Models—0
Taurus: A Data Plane Architecture for Per-Packet ML—0
Teacher Encoder-Student Decoder Denoising Guided Segmentation Network for Anomaly Detection—0
Teacher-Student Network for 3D Point Cloud Anomaly Detection with Few Normal Samples—0
TeG: Temporal-Granularity Method for Anomaly Detection with Attention in Smart City Surveillance—0
Template-guided Hierarchical Feature Restoration for Anomaly Detection—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