  When fonts are used on documents, they are intentionally selected by
designers. For example, when designing a book cover, the typography of the text
is an important factor in the overall feel of the book. In addition, it needs
to be an appropriate font for the rest of the book cover. Thus, we propose a
method of generating a book title image based on its context within a book
cover. We propose an end-to-end neural network that inputs the book cover, a
target location mask, and a desired book title and outputs stylized text
suitable for the cover. The proposed network uses a combination of a
multi-input encoder-decoder, a text skeleton prediction network, a perception
network, and an adversarial discriminator. We demonstrate that the proposed
method can effectively produce desirable and appropriate book cover text
through quantitative and qualitative results.
