35 citations · 60 across the 10 of their papers we have counts for
5 papers · 1 filter
Towards Real-World Focus Stacking with Deep Learning
Alexandre Araujo, Jean Ponce, Julien Mairal
Focus stacking is widely used in micro, macro, and landscape photography to reconstruct all-in-focus images from multiple frames obtained with focus bracketing, that is, with shall…
R-LPIPS: An Adversarially Robust Perceptual Similarity Metric
Sara Ghazanfari, Siddharth Garg, Prashanth Krishnamurthy +2
Similarity metrics have played a significant role in computer vision to capture the underlying semantics of images. In recent years, advanced similarity metrics, such as the Learne…
Towards Better Certified Segmentation via Diffusion Models
Othmane Laousy, Alexandre Araujo, Guillaume Chassagnon +4
The robustness of image segmentation has been an important research topic in the past few years as segmentation models have reached production-level accuracy. However, like classif…
Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability
Haotian Xue, Alexandre Araujo, Bin Hu +1
Neural networks are known to be susceptible to adversarial samples: small variations of natural examples crafted to deliberately mislead the models. While they can be easily genera…
Training compact deep learning models for video classification using circulant matrices
Alexandre Araujo, Benjamin Negrevergne, Yann Chevaleyre +1
In real world scenarios, model accuracy is hardly the only factor to consider. Large models consume more memory and are computationally more intensive, which makes them difficult t…