Wasserstein generative models for patch-based texture synthesis

DOI10.1007/978-3-030-75549-2_22zbMath1484.68297OpenAlexW3163262904MaRDI QIDQ826187

Arthur Leclaire, Antoine Houdard, Nicolas Papadakis, Julien Rabin

Publication date: 20 December 2021

Full work available at URL: https://doi.org/10.1007/978-3-030-75549-2_22

Mathematics Subject Classification ID

Random fields; image analysis (62M40) Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies for image processing (68U10)

Related Items (2)

A generative model for texture synthesis based on optimal transport between feature distributions ⋮ WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution

Cites Work

• Optimal transport for applied mathematicians. Calculus of variations, PDEs, and modeling
• A Nonlocal Bayesian Image Denoising Algorithm
• A Texture Synthesis Model Based on Semi-Discrete Optimal Transport in Patch Space
• High-Dimensional Mixture Models for Unsupervised Image Denoising (HDMI)
• A Review of Image Denoising Algorithms, with a New One

This page was built for publication: Wasserstein generative models for patch-based texture synthesis