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 726750 of 4856 papers

TitleStatusHype
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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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