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 701–750 of 4856 papers

TitleStatusHype
AnomalyR1: A GRPO-based End-to-end MLLM for Industrial Anomaly DetectionCode1
DeepTrust: A Reliable Financial Knowledge Retrieval Framework For Explaining Extreme Pricing AnomaliesCode1
Normality Learning-based Graph Anomaly Detection via Multi-Scale Contrastive LearningCode1
Delving into CLIP latent space for Video Anomaly RecognitionCode1
ICSML: Industrial Control Systems ML Framework for native inference using IEC 61131-3 codeCode1
Attention-based residual autoencoder for video anomaly detectionCode1
Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case StudyCode1
DenseHybrid: Hybrid Anomaly Detection for Dense Open-set RecognitionCode1
Anatomy-aware Self-supervised Learning for Anomaly Detection in Chest RadiographsCode1
DeScarGAN: Disease-Specific Anomaly Detection with Weak SupervisionCode1
Hybrid Open-set Segmentation with Synthetic Negative DataCode1
Identify Backdoored Model in Federated Learning via Individual UnlearningCode1
ADGym: Design Choices for Deep Anomaly DetectionCode1
Detecting Anomalies within Time Series using Local Neural TransformationsCode1
A General Framework For Detecting Anomalous Inputs to DNN ClassifiersCode1
Omni-frequency Channel-selection Representations for Unsupervised Anomaly DetectionCode1
On Data Fabrication in Collaborative Vehicular Perception: Attacks and CountermeasuresCode1
On Diffusion Modeling for Anomaly DetectionCode1
An Attention-guided Multistream Feature Fusion Network for Localization of Risky Objects in Driving VideosCode1
Anomaly Detection in Emails using Machine Learning and Header InformationCode1
HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural NetworksCode1
DFR: Deep Feature Reconstruction for Unsupervised Anomaly SegmentationCode1
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile RobotsCode1
Diffusion-Based Electrocardiography Noise Quantification via Anomaly DetectionCode1
HRN: A Holistic Approach to One Class LearningCode1
A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame PredictionCode1
A Discrepancy Aware Framework for Robust Anomaly DetectionCode1
Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain ImagesCode1
Anomaly Detection in Dynamic Graphs via TransformerCode1
A Novel Decomposed Feature-Oriented Framework for Open-Set Semantic Segmentation on LiDAR DataCode1
On the Effectiveness of Log Representation for Log-based Anomaly DetectionCode1
Optimal Reservoir Operations using Long Short-Term Memory NetworkCode1
ORAN-Bench-13K: An Open Source Benchmark for Assessing LLMs in Open Radio Access NetworksCode1
Out-of-Distribution Detection for Monocular Depth EstimationCode1
AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-DecoderCode1
Bootstrap Fine-Grained Vision-Language Alignment for Unified Zero-Shot Anomaly LocalizationCode1
HSTforU: anomaly detection in aerial and ground-based videos with hierarchical spatio-temporal transformer for U-netCode1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
AD-LLM: Benchmarking Large Language Models for Anomaly DetectionCode1
Dissolving Is Amplifying: Towards Fine-Grained Anomaly DetectionCode1
PatchAD: A Lightweight Patch-based MLP-Mixer for Time Series Anomaly DetectionCode1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
PNI : Industrial Anomaly Detection using Position and Neighborhood InformationCode1
Diversity-Measurable Anomaly DetectionCode1
Asymmetric Student-Teacher Networks for Industrial Anomaly DetectionCode1
Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public ProcurementCode1
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly DetectionCode1
Does Graph Distillation See Like Vision Dataset Counterpart?Code1
Peri-midFormer: Periodic Pyramid Transformer for Time Series AnalysisCode1
How To Backdoor Federated LearningCode1
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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