5 citations · 6 across the 3 of their papers we have counts for
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cs.CV2023★ 1 cited
Unsupervised Domain Adaption with Pixel-level Discriminator for Image-aware Layout Generation
Chenchen Xu, Min Zhou, Tiezheng Ge +2
Layout is essential for graphic design and poster generation. Recently, applying deep learning models to generate layouts has attracted increasing attention. This paper focuses on…
cs.CV2023
CF-Font: Content Fusion for Few-shot Font Generation
Chi Wang, Min Zhou, Tiezheng Ge +3
Content and style disentanglement is an effective way to achieve few-shot font generation. It allows to transfer the style of the font image in a source domain to the style defined…
cs.CV2022★ 5 cited
Composition-aware Graphic Layout GAN for Visual-textual Presentation Designs
Min Zhou, Chenchen Xu, Ye Ma +3
In this paper, we study the graphic layout generation problem of producing high-quality visual-textual presentation designs for given images. We note that image compositions, which…