Copyright Plug-in Market for The Text-to-Image Copyright Protection

Chao Zhou, Huishuai Zhang, Nenghai Yu, Jiang Bian

Primary Area: societal considerations including fairness, safety, privacy

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Keywords: generative model, copyright, text-to-image, LoRA

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Abstract: The images generated by text-to-image models could be accused of the copyright infringement, which has aroused heated debate among AI developers, content creators, legislation department and judicature department. Especially, the state-of-the-art text-to-image models are capable of generating extremely high-quality works while at the same time lack the ability to attribute credits to the original creators, which brings anxiety to the artists' community. In this paper, we propose a conceptual framework -- copyright Plug-in Market -- to address the tension between the users, the content creators and the generative models. We introduce three operations in the \copyright Plug-in Market: addition, extraction and combination to facilitate proper credit attribution in the text-to-image procedure and enable the digital copyright protection. For the addition operation, we train a \copyright plug-in for a specific copyrighted concept and add it to the generative model and then we are able to generate new images with the copyrighted concept, which abstract existing solutions of portable LoRAs. We further introduce the extraction operation to enable content creators to claim copyrighted concept from infringing generative models and the combination operation to enable users to combine different \copyright plug-ins to generate images with multiple copyrighted concepts. We believe these basic operations give good incentives to each participant in the market, and enable enough flexibility to thrive the market. Technically, we innovate an ``inverse LoRA'' approach to instantiate the extraction operation and propose a ``data-ignorant layer-wise distillation'' approach to combine the multiple extractions or additions easily. To showcase the diverse capabilities of copyright plug-ins, we conducted experiments in two domains: style transfer and cartoon IP recreation. The results demonstrate that copyright plug-ins can effectively accomplish copyright extraction and combination, providing a valuable copyright protection solution for the era of generative AIs.

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Submission Number: 5617