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Found 6 papers, 1 papers with code
Stochastic Super-Resolution For Gaussian Textures
The goal of this paper is to show that stochastic SR is a well-posed and solvable problem when restricting to Gaussian stationary textures.
On The Role of Alias and Band-Shift for Sentinel-2 Super-Resolution
In this work, we study the problem of single-image super-resolution (SISR) of Sentinel-2 imagery.
Scaling Painting Style Transfer
Neural style transfer is a deep learning technique that produces an unprecedentedly rich style transfer from a style image to a content image and is particularly impressive when it comes to transferring style from a painting to an image.
On Demand Solid Texture Synthesis Using Deep 3D Networks
Based on a few example images of textures, a generative network is trained to synthesize coherent portions of solid textures of arbitrary sizes that reproduce the visual characteristics of the examples along some directions.
Maximum entropy methods for texture synthesis: theory and practice
Recent years have seen the rise of convolutional neural network techniques in exemplar-based image synthesis.
Exact Sampling of Determinantal Point Processes without Eigendecomposition
The exact algorithm to sample DPPs uses the spectral decomposition of $K$, a computation that becomes costly when dealing with a high number of points.
