Specific Papers
===============
* | https://arxiv.org/abs/1505.07376
  | **Texture Synthesis Using Convolutional Neural Networks**
* | https://arxiv.org/abs/1508.06576
  | A Neural Algorithm of Artistic Style
* | https://arxiv.org/abs/1603.03417
  | **Texture Networks: Feed-forward Synthesis of Textures and Stylized Images**
* | https://arxiv.org/abs/1701.02096
  | Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Texture Synthesis
* | https://arxiv.org/abs/1601.04589
  | **Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis**
* | https://arxiv.org/abs/1601.04589
  | Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks
* | https://arxiv.org/abs/1705.01088
  | **Visual Attribute Transfer through Deep Image Analogy**
* | https://arxiv.org/abs/1703.06868
  | Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
* | https://arxiv.org/abs/1911.06953
  | Dynamic Instance Normalization for Arbitrary Style Transfer
* | https://arxiv.org/abs/1811.05621
  | Style and Content Disentanglement in Generative Adversarial Networks
* | https://arxiv.org/abs/1805.04487
  | Non-Stationary Texture Synthesis by Adversarial Expansion
* | https://arxiv.org/abs/1807.11035
  | Texture Mixing by Interpolating Deep Statistics via Gaussian Models
* | https://arxiv.org/abs/1612.04337
  | **Fast Patch-based Style Transfer of Arbitrary Style**
* | https://arxiv.org/abs/1705.08086
  | Universal Style Transfer via Feature Transforms
* | https://arxiv.org/abs/1612.01895
  | Multimodal Transfer: A Hierarchical Deep Convolutional Neural Network for Fast Artistic Style Transfer
* | https://arxiv.org/abs/2009.01376
  | NITES: A Non-Parametric Interpretable Texture Synthesis Method

Classics
========
* | https://www.microsoft.com/en-us/research/publication/inverse-texture-synthesis/
  | Inverse Texture Synthesis

Community Suggestions
=====================
* | https://arxiv.org/abs/2007.07243
  | Transposer: Universal Texture Synthesis Using Feature Maps as Transposed Convolution Filter
* | https://papers.nips.cc/paper/2020/file/a23156abfd4a114c35b930b836064e8b-Paper.pdf
  | **Neural FFTs for Universal Texture Image Synthesis**
* | https://arxiv.org/abs/1606.00021
  | Texture Synthesis Using Shallow Convolutional Networks with Random Filters
* | https://arxiv.org/abs/1611.08207
  | Texture Synthesis with Spatial Generative Adversarial Networks
* | https://arxiv.org/abs/1705.06566
  | Learning Texture Manifolds with the Periodic Spatial GAN
* | https://arxiv.org/abs/2001.04528
  | On Demand Solid Texture Synthesis Using Deep 3D Networks
* | https://arxiv.org/abs/1807.10201
  | A Style-Aware Content Loss for Real-time HD Style Transfer
* | https://arxiv.org/abs/2010.14702
  | **Optimal Textures: Fast and Robust Texture Synthesis and Style Transfer through Optimal Transport**

Reviews & Collections
=====================
* | https://arxiv.org/abs/1707.07184
  | **A Survey of Exemplar-based Texture Synthesis**
* | https://arxiv.org/abs/1705.04058
  | Neural Style Transfer: A Review
* | http://arxiv-sanity.com/1601.04589
  | (see list of papers related by keywords)