Preserving Color in Neural Artistic Style Transfer
Leon A. Gatys, Matthias Bethge, Aaron Hertzmann, Eli Shechtman

TL;DR
This paper introduces simple linear methods to enhance neural artistic style transfer by preserving original image colors, addressing a key shortcoming of the original algorithm.
Contribution
It proposes novel linear techniques for color preservation in neural style transfer, improving the visual fidelity of stylized images.
Findings
Color preservation methods effectively maintain original scene colors.
The proposed techniques are simple and easily integrated into existing algorithms.
Enhanced style transfer results with better color fidelity.
Abstract
This note presents an extension to the neural artistic style transfer algorithm (Gatys et al.). The original algorithm transforms an image to have the style of another given image. For example, a photograph can be transformed to have the style of a famous painting. Here we address a potential shortcoming of the original method: the algorithm transfers the colors of the original painting, which can alter the appearance of the scene in undesirable ways. We describe simple linear methods for transferring style while preserving colors.
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Taxonomy
TopicsAesthetic Perception and Analysis · Generative Adversarial Networks and Image Synthesis · Computer Graphics and Visualization Techniques
