Image analogies

In many contexts, painting and illustration have many advantages over photorealistic computer graphics, in aspects such as aesthetics, expression, and computational requirements.

Source: http://mrl.nyu.edu/projects/image-analogies/

the code could be downloaded here

Wikipedia: An “image analogy” is a method of creating an image filter automatically from training data. In an image analogy process, the transformation between two images A and A’ is “learned”. Later, given a different image B, it’s “analogy” image B’ can be generated based on the learned transformation. The image analogy method has been used to simulate many types of image filters:

  • Toy filters, such as blurring or “embossing.”
  • Texture synthesis from an example texture.
  • Super-resolution, inferring a high-resolution image from a low-resolutinon source.
  • Texture transfer, in which images are “texturized” with some arbitrary source texture.
  • Artistic filters, in which various drawing and painting styles, including oil, pastel, and pen-and-ink rendering, are synthesized based on scanned real-world examples.
  • Texture-by-numbers, in which realistic scenes, composed of a variety of textures, are created using a simple “painting” interface.
  • Image colorization, where color is automatically added to grayscale images.
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