Towards Book Cover Design via Layout Graphs

• URL: http://arxiv.org/abs/2105.11088v1
• Date: Mon, 24 May 2021 04:28:35 GMT
• Title: Towards Book Cover Design via Layout Graphs
• Authors: Wensheng Zhang, Yan Zheng, Taiga Miyazono, Seiichi Uchida, Brian Kenji Iwana
• Abstract summary: We propose a generative neural network that can produce book covers based on an easy-to-use layout graph. The layout graph contains objects such as text, natural scene objects, and solid color spaces.
• Score: 18.028269880425455
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Book covers are intentionally designed and provide an introduction to a book. However, they typically require professional skills to design and produce the cover images. Thus, we propose a generative neural network that can produce book covers based on an easy-to-use layout graph. The layout graph contains objects such as text, natural scene objects, and solid color spaces. This layout graph is embedded using a graph convolutional neural network and then used with a mask proposal generator and a bounding-box generator and filled using an object proposal generator. Next, the objects are compiled into a single image and the entire network is trained using a combination of adversarial training, perceptual training, and reconstruction. Finally, a Style Retention Network (SRNet) is used to transfer the learned font style onto the desired text. Using the proposed method allows for easily controlled and unique book covers.

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