{"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/c-plug-in-authorization-for-human-content","title":"©Plug-in Authorization for Human Content Copyright Protection in Text-to-Image Model","arxiv_id":"2404.11962","date":"2024-04-18","proceeding":null,"authors":["Chao Zhou","Huishuai Zhang","Jiang Bian","Weiming Zhang","Nenghai Yu"],"abstract":"This paper addresses the contentious issue of copyright infringement in images generated by text-to-image models, sparking debates among AI developers, content creators, and legal entities. State-of-the-art models create high-quality content without crediting original creators, causing concern in the artistic community. To mitigate this, we propose the \\copyright Plug-in Authorization framework, introducing three operations: addition, extraction, and combination. Addition involves training a \\copyright plug-in for specific copyright, facilitating proper credit attribution. Extraction allows creators to reclaim copyright from infringing models, and combination enables users to merge different \\copyright plug-ins. These operations act as permits, incentivizing fair use and providing flexibility in authorization. We present innovative approaches,\"Reverse LoRA\" for extraction and \"EasyMerge\" for seamless combination. Experiments in artist-style replication and cartoon IP recreation demonstrate \\copyright plug-ins' effectiveness, offering a valuable solution for human copyright protection in the age of generative AIs. The code is available at https://github.com/zc1023/-Plug-in-Authorization.git.","url_abs":"https://arxiv.org/abs/2404.11962v2","url_pdf":"https://arxiv.org/pdf/2404.11962v2.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":"c-plug-in-authorization-for-human-content","repo_url":"https://github.com/zc1023/-plug-in-authorization","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}