{"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/artist-style-transfer-via-quadratic-potential","title":"Artist Style Transfer Via Quadratic Potential","arxiv_id":"1902.11108","date":"2019-02-14","proceeding":null,"authors":["Rahul Bhalley","Jianlin Su"],"abstract":"In this paper we address the problem of artist style transfer where the\npainting style of a given artist is applied on a real world photograph. We\ntrain our neural networks in adversarial setting via recently introduced\nquadratic potential divergence for stable learning process. To further improve\nthe quality of generated artist stylized images we also integrate some of the\nrecently introduced deep learning techniques in our method. To our best\nknowledge this is the first attempt towards artist style transfer via quadratic\npotential divergence. We provide some stylized image samples in the\nsupplementary material. The source code for experimentation was written in\nPyTorch and is available online in my GitHub repository.","url_abs":"http://arxiv.org/abs/1902.11108v2","url_pdf":"http://arxiv.org/pdf/1902.11108v2.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":"artist-style-transfer-via-quadratic-potential","repo_url":"https://github.com/rahulbhalley/cyclegan-qp","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"style-transfer","task_name":"Style Transfer"}],"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}