25 citations · 44 across the 10 of their papers we have counts for
11 papers
SGSST: Scaling Gaussian Splatting StyleTransfer
Bruno Galerne, Jianling Wang, Lara Raad +1
Applying style transfer to a full 3D environment is a challenging task that has seen many developments since the advent of neural rendering. 3D Gaussian splatting (3DGS) has recent…
Adapting MIMO video restoration networks to low latency constraints
Valéry Dewil, Zhe Zheng, Arnaud Barral +7
MIMO (multiple input, multiple output) approaches are a recent trend in neural network architectures for video restoration problems, where each network evaluation produces multiple…
Stochastic Super-Resolution For Gaussian Textures
Emile Pierret, Bruno Galerne
Super-resolution (SR) is an ill-posed inverse problem which consists in proposing high-resolution images consistent with a given low-resolution one. While most SR algorithms are de…
On The Role of Alias and Band-Shift for Sentinel-2 Super-Resolution
Ngoc Long Nguyen, Jérémy Anger, Lara Raad +2
In this work, we study the problem of single-image super-resolution (SISR) of Sentinel-2 imagery. We show that thanks to its unique sensor specification, namely the inter-band shif…
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…
On Demand Solid Texture Synthesis Using Deep 3D Networks
Jorge Gutierrez, Julien Rabin, Bruno Galerne +1
This paper describes a novel approach for on demand volumetric texture synthesis based on a deep learning framework that allows for the generation of high quality 3D data at intera…
Maximum entropy methods for texture synthesis: theory and practice
Valentin De Bortoli, Agnes Desolneux, Alain Durmus +2
Recent years have seen the rise of convolutional neural network techniques in exemplar-based image synthesis. These methods often rely on the minimization of some variational formu…
Patch redundancy in images: a statistical testing framework and some applications
De Bortoli Valentin, Desolneux Agnès, Galerne Bruno +1
In this work we introduce a statistical framework in order to analyze the spatial redundancy in natural images. This notion of spatial redundancy must be defined locally and thus w…
Macrocanonical Models for Texture Synthesis
De Bortoli Valentin, Desolneux Agnès, Galerne Bruno +1
In this article we consider macrocanonical models for texture synthesis. In these models samples are generated given an input texture image and a set of features which should be ma…
Exact Sampling of Determinantal Point Processes without Eigendecomposition
Claire Launay, Bruno Galerne, Agnès Desolneux
Determinantal point processes (DPPs) enable the modeling of repulsion: they provide diverse sets of points. The repulsion is encoded in a kernel that can be seen as a matrix st…
Random Measurable Sets and Covariogram Realisability Problems
Bruno Galerne, Raphael Lachieze-Rey
We provide a characterization of the realisable set covariograms, bringing a rigorous yet abstract solution to the problem in materials science. Our method is based on the c…