54 citations · 226 across the 24 of their papers we have counts for
18 papers · 1 filter
Collaborative Blind Image Deblurring
Thomas Eboli, Jean-Michel Morel, Gabriele Facciolo
Blurry images usually exhibit similar blur at various locations across the image domain, a property barely captured in nowadays blind deblurring neural networks. We show that when…
Scaling Painting Style Transfer
Bruno Galerne, Lara Raad, José Lezama +1
Neural style transfer (NST) is a deep learning technique that produces an unprecedentedly rich style transfer from a style image to a content image. It is particularly impressive w…
Can neural networks extrapolate? Discussion of a theorem by Pedro Domingos
Adrien Courtois, Jean-Michel Morel, Pablo Arias
Neural networks trained on large datasets by minimizing a loss have become the state-of-the-art approach for resolving data science problems, particularly in computer vision, image…
Investigating Neural Architectures by Synthetic Dataset Design
Adrien Courtois, Jean-Michel Morel, Pablo Arias
Recent years have seen the emergence of many new neural network structures (architectures and layers). To solve a given task, a network requires a certain set of abilities reflecte…
Joint Demosaicking and Denoising Benefits from a Two-stage Training Strategy
Yu Guo, Qiyu Jin, Gabriele Facciolo +2
Image demosaicking and denoising are the first two key steps of the color image production pipeline. The classical processing sequence has for a long time consisted of applying den…
Reducing Anomaly Detection in Images to Detection in Noise
Axel Davy, Thibaud Ehret, Jean-Michel Morel +1
Anomaly detectors address the difficult problem of detecting automatically exceptions in an arbitrary background image. Detection methods have been proposed by the thousands becaus…