A multi-image diffusion stylization pipeline that averages style embeddings, fine-tunes an IPAdapter, and clusters self-attention key/value features from style images achieves state-of-the-art scores on a new style-transfer test set.
Aladin-nst: Self-supervised disentangled representation learning of artistic style through neural style transfer, 2023
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Leveraging Diffusion Models for Stylization using Multiple Style Images
A multi-image diffusion stylization pipeline that averages style embeddings, fine-tunes an IPAdapter, and clusters self-attention key/value features from style images achieves state-of-the-art scores on a new style-transfer test set.