Recent advancements in computer vision have enabled wide-ranging applications in every
field of life. One such application area is fresh produce classification, but the classification of …

The recent work of Gatys et al., who characterized the style of an image by the statistics of
convolutional neural network filters, ignited a renewed interest in the texture generation and …

Texture is a fundamental characteristic of many types of images, and texture representation
is one of the essential and challenging problems in computer vision and pattern recognition …

An ever-growing number of real-world computer vision applications require classification,
segmentation, retrieval, or realistic rendering of genuine materials. However, the …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

This book provides a self-contained and up-to-date treatment of the Monte Carlo method
and develops a common framework under which various Monte Carlo techniques can be" …

We present a universal statistical model for texture images in the context of an overcomplete
complex wavelet transform. The model is parameterized by a set of statistics computed on …

We present an algorithm for synthesizing textures from an input sample. This patch-based
sampling algorithm is fast and it makes high-quality texture synthesis a real-time process …

Image style transfer is an underdetermined problem, where a large number of solutions can
satisfy the same constraint (the content and style). Although there have been some efforts to …

Many low-level vision algorithms assume a prior probability over images, and there has
been great interest in trying to learn this prior from examples. Since images are very non …