Публікація: A survey of methods of text-to-image translation
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Дата
2019
Автори
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ХНУРЕ
Анотація
The given work considers the existing methods of text compression (finding keywords or creating summary) using RAKE, Lex Rank, Luhn, LSA, Text Rank algorithms; image generation; text-to-image and image-to-image translation
including GANs (generative adversarial networks). Different types of GANs were described such as StyleGAN, GauGAN, Pix2Pix, CycleGAN, BigGAN, AttnGAN. This work aims to show ways to create illustrations for the text. First, key
information should be obtained from the text. Second, this key information should be transformed into images. There were proposed several ways to transform keywords to images: generating images or selecting them from a dataset with further transforming like generating new images based on selected ow combining selected images e.g. with applying style from one image to another. Based on results, possibilities for further improving the quality of image generation were also planned: combining image generation with selecting images from a dataset, limiting topics of image generation.
Опис
Ключові слова
Image generation, Text keywords, Image-to-image translation, Text-to-image translation, Text compression
Бібліографічний опис
Konarieva I. A survey of methods of text-to-image translation / Konarieva I., Pydorenko D., Turuta O. // Бионика интеллекта : научно-технический журнал. – 2019. – № 2 (93). – С. 64–68.