HyperAI

Anomaly Detection On Mpdd

Metrics

Detection AUROC
Segmentation AUROC

Results

Performance results of various models on this benchmark

Model Name
Detection AUROC
Segmentation AUROC
Paper TitleRepository
GLAD97.598.7GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection
LeMO87.497.8Towards Total Online Unsupervised Anomaly Detection and Localization in Industrial Vision-
AdaCLIP82.596.1AdaCLIP: Adapting CLIP with Hybrid Learnable Prompts for Zero-Shot Anomaly Detection
ADSPR-96.8Anomaly Detection using Score-based Perturbation Resilience
PatchCore82.1295.66Towards Total Recall in Industrial Anomaly Detection
ULSAD95.7397.45Revisiting Deep Feature Reconstruction for Logical and Structural Industrial Anomaly Detection
DMDD98.1098.96Dual-Modeling Decouple Distillation for Unsupervised Anomaly Detection-
FastRecon82.597.9FastRecon: Few-shot Industrial Anomaly Detection via Fast Feature Reconstruction-
DiffusionAD96.298.5DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection
POUTA97.5-Produce Once, Utilize Twice for Anomaly Detection-
GLASS99.699.4A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization
Dinomaly97.299.1Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection
KAnoCLIP77.898.3KAnoCLIP: Zero-Shot Anomaly Detection through Knowledge-Driven Prompt Learning and Enhanced Cross-Modal Integration-
RealNet96.398.2RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection
PBAS97.798.8Progressive Boundary Guided Anomaly Synthesis for Industrial Anomaly Detection
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