MaTe proposes a training-free diffusion transformer that performs material transfer using only images by integrating them at the token level for unified multi-modal attention in a shared latent space.
Prospect: Prompt spectrum for attribute-aware personalization of diffusion models.ACM Transactions on Graphics (ToG), 42(6):1–14, 2023
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MaTe: Images Are All You Need for Material Transfer via Diffusion Transformer
MaTe proposes a training-free diffusion transformer that performs material transfer using only images by integrating them at the token level for unified multi-modal attention in a shared latent space.