Learning Profitable NFT Image Diffusions via Multiple Visual-Policy Guided Reinforcement Learning

Understand

We study the task of generating profitable Non-Fungible Token (NFT) images from user-input texts.

• Recent advances in diffusion models have shown great potential for image generation.
• However, existing works can fall short in generating visually-pleasing and highly-profitable NFT images, mainly due to the lack of 1) plentiful and fine-grained visual attribute prompts for an NFT image, and 2) effective optimization metrics for generating high-quality NFT images.
• To solve these challenges, we propose a Diffusion-based generation framework with Multiple Visual-Policies as rewards (i.e., Diffusion-MVP) for NFT images.