Abstract
Among the problems of specifying the style and number of elements of a travel magazine, the problem of generating magazine layout by constraining text, and constraining graph layout remains a complex and unsolved problem. In this paper, we generate layouts of text satisfying constraints via GAN. Due to the complexity and variety of graph designs, we enhance the performance of the discriminator and the generator so that the layouts generated by the generator are more constrained. Add non-corresponding constraint text and real layout pairs to the discriminator to enhance the performance of the discriminator; then add a spatial attention mechanism to the layout encoder to extract the features of the layout and generate high-quality layouts. We demonstrate that the proposed method can generate high-quality layouts of text satisfying the constraints, and we validate the effectiveness of this method through user ratings.
Published Version
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