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

Showing 826850 of 4856 papers

TitleStatusHype
A SAM-guided Two-stream Lightweight Model for Anomaly DetectionCode1
RAD: A Dataset and Benchmark for Real-Life Anomaly Detection with Robotic ObservationsCode1
Rail Detection: An Efficient Row-based Network and A New BenchmarkCode1
Random Partitioning Forest for Point-Wise and Collective Anomaly Detection -- Application to Intrusion DetectionCode1
RAPID: Training-free Retrieval-based Log Anomaly Detection with PLM considering Token-level informationCode1
Real-Time Anomaly Detection in Edge StreamsCode1
A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in VideoCode1
Anomal-E: A Self-Supervised Network Intrusion Detection System based on Graph Neural NetworksCode1
REB: Reducing Biases in Representation for Industrial Anomaly DetectionCode1
Reconstruction-Free Anomaly Detection with Diffusion Models via Direct Latent Likelihood EvaluationCode1
Reconstruction from edge image combined with color and gradient difference for industrial surface anomaly detectionCode1
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR ImagesCode1
Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly DetectionCode1
Broiler-Net: A Deep Convolutional Framework for Broiler Behavior Analysis in Poultry HousesCode1
Boosting Fine-Grained Visual Anomaly Detection with Coarse-Knowledge-Aware Adversarial LearningCode1
BSDM: Background Suppression Diffusion Model for Hyperspectral Anomaly DetectionCode1
Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic SegmentationCode1
Adversarial Anomaly Detection using Gaussian Priors and Nonlinear Anomaly ScoresCode1
Revisiting Deep Ensemble Uncertainty for Enhanced Medical Anomaly DetectionCode1
Camouflaged Object DetectionCode1
Road Anomaly Detection by Partial Image Reconstruction With Segmentation CouplingCode1
Binary Noise for Binary Tasks: Masked Bernoulli Diffusion for Unsupervised Anomaly DetectionCode1
Beyond Outlier Detection: Outlier Interpretation by Attention-Guided Triplet Deviation NetworkCode1
RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous SupervisionCode1
BIVA: A Very Deep Hierarchy of Latent Variables for Generative ModelingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016Unverified
2CPR-fast(TensorRT)FPS362Unverified
3CPR(TensorRT)FPS130Unverified
4GLASSDetection AUROC99.9Unverified
5UniNetDetection AUROC99.9Unverified
6HETMMDetection AUROC99.8Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9DDADDetection AUROC99.8Unverified
10PBASDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
5DDADDetection AUROC98.9Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9Unverified
7DiffusionADDetection AUROC98.8Unverified
8GLASSDetection AUROC98.8Unverified
9TransFusionDetection AUROC98.7Unverified
10HETMMDetection AUROC98.1Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3Unverified
2PSADAvg. Detection AUROC94.9Unverified