{"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/example-guided-style-consistent-image-1","title":"Example-Guided Style Consistent Image Synthesis from Semantic Labeling","arxiv_id":"1906.01314","date":"2019-06-04","proceeding":null,"authors":["Miao Wang","Guo-Ye Yang","Rui-Long Li","Run-Ze Liang","Song-Hai Zhang","Peter. M. Hall","Shi-Min Hu"],"abstract":"Example-guided image synthesis aims to synthesize an image from a semantic label map and an exemplary image indicating style. We use the term \"style\" in this problem to refer to implicit characteristics of images, for example: in portraits \"style\" includes gender, racial identity, age, hairstyle; in full body pictures it includes clothing; in street scenes, it refers to weather and time of day and such like. A semantic label map in these cases indicates facial expression, full body pose, or scene segmentation. We propose a solution to the example-guided image synthesis problem using conditional generative adversarial networks with style consistency. Our key contributions are (i) a novel style consistency discriminator to determine whether a pair of images are consistent in style; (ii) an adaptive semantic consistency loss; and (iii) a training data sampling strategy, for synthesizing style-consistent results to the exemplar.","url_abs":"https://arxiv.org/abs/1906.01314v2","url_pdf":"https://arxiv.org/pdf/1906.01314v2.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":"example-guided-style-consistent-image-1","repo_url":"https://github.com/cxjyxxme/pix2pixSC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"image-generation","task_name":"Image Generation"},{"task_slug":"scene-segmentation","task_name":"Scene Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1906.01314","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}