Existing example-based texture synthesis techniques are inherently unadapted to textures consisting of a set of randomly disposed, individually discernible shapes. Local methods striving at pixel-based discontinuity reduction hardly preserve input’s long-range structures. Alternatively, research built upon the supposed respect by the input’s features of given placement rules are too restrictive...

Abstract As image generation techniques mature, there is a growing interest in explainable representations that are easy to understand and intuitive manipulate. In this work, we turn co-occurrence statistics, which have long been used for texture analysis, learn controllable synthesis model. We propose fully convolutional generative adversarial network, conditioned locally on generate arbitrari...

In image processing, a static texture is defined as an image showing spatial stationarity, while A dynamic texture is a sequence of images characterized by temporal as well as spatial stationary nature. Dynamic Texture synthesis is the process of producing artificial Dynamic textures starting from a given sample texture. Videos representing flames, water, smoke, etc. are often defined as dynami...

Three-dimensional (3D) textures are popular for texturing solid objects. They usually achieve superior results over conventional two-dimensional (2D) texture mapping techniques. However, whereas 2D textures can be obtained using for example a photograph, capturing or generating solid textures is not straightforward. Procedural techniques can replicate some types of materials, but are usually di...

Synthesis of textures is a very popular and active area of research; the applications and the areas of interest are various and significant. In the last years, much work has been done in order to optimize the synthesis process, speeding up the methods and minimizing the processing errors. Recent efforts in this area are concentrated in producing flexible algorithms and in introducing tools, whi...