{"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/artistic-style-transfer-for-videos","title":"Artistic style transfer for videos","arxiv_id":"1604.08610","date":"2016-04-28","proceeding":null,"authors":["Manuel Ruder","Alexey Dosovitskiy","Thomas Brox"],"abstract":"In the past, manually re-drawing an image in a certain artistic style\nrequired a professional artist and a long time. Doing this for a video sequence\nsingle-handed was beyond imagination. Nowadays computers provide new\npossibilities. We present an approach that transfers the style from one image\n(for example, a painting) to a whole video sequence. We make use of recent\nadvances in style transfer in still images and propose new initializations and\nloss functions applicable to videos. This allows us to generate consistent and\nstable stylized video sequences, even in cases with large motion and strong\nocclusion. We show that the proposed method clearly outperforms simpler\nbaselines both qualitatively and quantitatively.","url_abs":"http://arxiv.org/abs/1604.08610v2","url_pdf":"http://arxiv.org/pdf/1604.08610v2.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":"artistic-style-transfer-for-videos","repo_url":"https://github.com/manuelruder/artistic-videos","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"torch","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"artistic-style-transfer-for-videos","repo_url":"https://github.com/anitagold/60-days-of-Udacity","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"artistic-style-transfer-for-videos","repo_url":"https://github.com/cysmith/neural-style-tf","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[{"task_slug":"style-transfer","task_name":"Style Transfer"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1604.08610","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}