156 citations · 219 across the 12 of their papers we have counts for
4 papers · 1 filter
Self-Supervised Iterative Refinement for Anomaly Detection in Industrial Quality Control
Muhammad Aqeel, Shakiba Sharifi, Marco Cristani +1
This study introduces the Iterative Refinement Process (IRP), a robust anomaly detection methodology designed for high-stakes industrial quality control. The IRP enhances defect de…
Enhancing Split Computing and Early Exit Applications through Predefined Sparsity
Luigi Capogrosso, Enrico Fraccaroli, Giulio Petrozziello +4
In the past decade, Deep Neural Networks (DNNs) achieved state-of-the-art performance in a broad range of problems, spanning from object classification and action recognition to sm…
Leveraging Latent Diffusion Models for Training-Free In-Distribution Data Augmentation for Surface Defect Detection
Federico Girella, Ziyue Liu, Franco Fummi +3
Defect detection is the task of identifying defects in production samples. Usually, defect detection classifiers are trained on ground-truth data formed by normal samples (negative…
Diffusion-based Image Generation for In-distribution Data Augmentation in Surface Defect Detection
Luigi Capogrosso, Federico Girella, Francesco Taioli +5
In this study, we show that diffusion models can be used in industrial scenarios to improve the data augmentation procedure in the context of surface defect detection. In general,…