{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/gilt-generating-images-from-long-text","title":"GILT: Generating Images from Long Text","arxiv_id":"1901.02404","date":"2019-01-08","proceeding":null,"authors":["Ori Bar El","Ori Licht","Netanel Yosephian"],"abstract":"Creating an image reflecting the content of a long text is a complex process\nthat requires a sense of creativity. For example, creating a book cover or a\nmovie poster based on their summary or a food image based on its recipe. In\nthis paper we present the new task of generating images from long text that\ndoes not describe the visual content of the image directly. For this, we build\na system for generating high-resolution 256 $\\times$ 256 images of food\nconditioned on their recipes. The relation between the recipe text (without its\ntitle) to the visual content of the image is vague, and the textual structure\nof recipes is complex, consisting of two sections (ingredients and\ninstructions) both containing multiple sentences.\n  We used the recipe1M dataset to train and evaluate our model that is based on\na the StackGAN-v2 architecture.","url_abs":"http://arxiv.org/abs/1901.02404v1","url_pdf":"http://arxiv.org/pdf/1901.02404v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"gilt-generating-images-from-long-text","repo_url":"https://github.com/netanelyo/Recipe2ImageGAN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}