19 citations · 46 across the 8 of their papers we have counts for
8 papers
A Hybrid Neural-Microfacet BRDF Model for Real-Time Rendering
Louis De Oliveira, Anastasia Karpova, Georges Nader +4
Over the past decade, microfacet-based BRDF models have formed the foundation of real-time rendering pipelines. Despite their widespread use, they often fail to reproduce subtle ap…
Real-Time Neural Materials using Block-Compressed Features
Clément Weinreich, Louis de Oliveira, Antoine Houdard +1
Neural materials typically consist of a collection of neural features along with a decoder network. The main challenge in integrating such models in real-time rendering pipelines l…
Inverse problem regularization with hierarchical variational autoencoders
Jean Prost, Antoine Houdard, Andrés Almansa +1
In this paper, we propose to regularize ill-posed inverse problems using a deep hierarchical variational autoencoder (HVAE) as an image prior. The proposed method synthesizes the a…
Diverse super-resolution with pretrained deep hiererarchical VAEs
Jean Prost, Antoine Houdard, Andrés Almansa +1
We investigate the problem of producing diverse solutions to an image super-resolution problem. From a probabilistic perspective, this can be done by sampling from the posterior di…
Wasserstein Patch Prior for Image Superresolution
Johannes Hertrich, Antoine Houdard, Claudia Redenbach
In this paper, we introduce a Wasserstein patch prior for superresolution of two- and three-dimensional images. Here, we assume that we have given (additionally to the low resoluti…
Learning local regularization for variational image restoration
Jean Prost, Antoine Houdard, Andrés Almansa +1
In this work, we propose a framework to learn a local regularization model for solving general image restoration problems. This regularizer is defined with a fully convolutional ne…
On the Existence of Optimal Transport Gradient for Learning Generative Models
Antoine Houdard, Arthur Leclaire, Nicolas Papadakis +1
The use of optimal transport cost for learning generative models has become popular with Wasserstein Generative Adversarial Networks (WGAN). Training of WGAN relies on a theoretica…
A Generative Model for Texture Synthesis based on Optimal Transport between Feature Distributions
Antoine Houdard, Arthur Leclaire, Nicolas Papadakis +1
We propose GOTEX, a general framework for texture synthesis by optimization that constrains the statistical distribution of local features. While our model encompasses several exis…