CAMS: Color-Aware Multi-Style Transfer

• URL: http://arxiv.org/abs/2106.13920v1
• Date: Sat, 26 Jun 2021 01:15:09 GMT
• Title: CAMS: Color-Aware Multi-Style Transfer
• Authors: Mahmoud Afifi, Abdullah Abuolaim, Mostafa Hussien, Marcus A. Brubaker, Michael S. Brown
• Abstract summary: Style transfer aims to manipulate the appearance of a source image, or "content" image, to share similar texture and colors of a target "style" image. A commonly used approach to assist in transferring styles is based on Gram matrix optimization. We propose a color-aware multi-style transfer method that generates aesthetically pleasing results while preserving the style-color correlation between style and generated images.
• Score: 46.550390398057985
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Image style transfer aims to manipulate the appearance of a source image, or "content" image, to share similar texture and colors of a target "style" image. Ideally, the style transfer manipulation should also preserve the semantic content of the source image. A commonly used approach to assist in transferring styles is based on Gram matrix optimization. One problem of Gram matrix-based optimization is that it does not consider the correlation between colors and their styles. Specifically, certain textures or structures should be associated with specific colors. This is particularly challenging when the target style image exhibits multiple style types. In this work, we propose a color-aware multi-style transfer method that generates aesthetically pleasing results while preserving the style-color correlation between style and generated images. We achieve this desired outcome by introducing a simple but efficient modification to classic Gram matrix-based style transfer optimization. A nice feature of our method is that it enables the users to manually select the color associations between the target style and content image for more transfer flexibility. We validated our method with several qualitative comparisons, including a user study conducted with 30 participants. In comparison with prior work, our method is simple, easy to implement, and achieves visually appealing results when targeting images that have multiple styles. Source code is available at https://github.com/mahmoudnafifi/color-aware-style-transfer.

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