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Texture synthesis is the process of algorithmically constructing a large digital image from a small digital sample image by taking advantage of its structural content. It is an object of research in computer graphics and is used in many fields, amongst others digital image editing, 3D computer graphics and post-production of films.
NST is an example of image stylization, a problem studied for over two decades within the field of non-photorealistic rendering. The first two example-based style transfer algorithms were image analogies [1] and image quilting. [2] Both of these methods were based on patch-based texture synthesis algorithms.
Simplified example of training a neural network in object detection: The network is trained by multiple images that are known to depict starfish and sea urchins, which are correlated with "nodes" that represent visual features. The starfish match with a ringed texture and a star outline, whereas most sea urchins match with a striped texture and ...
A neural radiance field (NeRF) is a method based on deep learning for reconstructing a three-dimensional representation of a scene from two-dimensional images. The NeRF model enables downstream applications of novel view synthesis, scene geometry reconstruction, and obtaining the reflectance properties of the scene. Additional scene properties ...
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A texture map [5] [6] is an image applied (mapped) to the surface of a shape or polygon. [7] This may be a bitmap image or a procedural texture.They may be stored in common image file formats, referenced by 3D model formats or material definitions, and assembled into resource bundles.
In the example to the right, a sphere is given a checkered texture in two ways. On the left, without UV mapping, the sphere is carved out of three-dimensional checkers tiling Euclidean space. With UV mapping, the checkers tile the two-dimensional UV space, and points on the sphere map to this space according to their latitude and longitude.