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- W4381196525 abstract "This paper presents a new font shape style transfer technique that employs a generative adversarial network (GAN) and skeleton-based input feature maps to modify a target text to match a target font shape while retaining the original text content. Our GAN model is modified from a Shape-Matching GAN which utilizes a StyleNet generator and a PatchGAN discriminator. Rather than using a base-font character images as input to the generator like other existing font transfer models, we utilize the proposed skeleton-based features as input. The experimental results show that our model can produce the unseen characters in the desired font style better than an existing method." @default.
- W4381196525 created "2023-06-20" @default.
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- W4381196525 date "2023-04-28" @default.
- W4381196525 modified "2023-09-25" @default.
- W4381196525 title "Skeleton-based Generative Adversarial Networks for Font Shape Style Transfer" @default.
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- W4381196525 doi "https://doi.org/10.1145/3596286.3596288" @default.
- W4381196525 hasPublicationYear "2023" @default.
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