Controllable and Personalized Non-fungible Tokens (NFT) Art Creation with Generative AI
PI: Dr Xihui LIU
Abstract:
NFT art is a form of digital art that is authenticated and traded on a blockchain network. The recent success of diffusion models for image generation has empowered AI for NFT art creation. In recent years, several AI-created NFT artworks have been sold for high prices at auctions and marketplaces. However, the AI-created NFT art still faces many challenges, such as the difficulty of aligning the generated content with the market demand, and the limited control and personalization options for the users. In this project, our main objectives are: (1) to propose an algorithm to efficiently align the diffusion-based generative model with the NFT art pricing market; (2) to introduce a unified framework for fine-grained controllable and personalized NFT art generation based on the backbone of Stable Diffusion; and (3) to extend the proposed algorithms to NFT gif or video creation and NFT 3D character creation. Our project will have significant impacts for both academia and industry, as it will push the boundary of NFT art research and generative AI research, as well as create numerous applications and opportunities for various sectors, such as gaming industry, designing products, and entertainment.