AI RESEARCH
StyleVAR: Controllable Image Style Transfer via Visual Autoregressive Modeling
arXiv CS.CV
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ArXi:2604.21052v1 Announce Type: new We build on the Visual Autoregressive Modeling (VAR) framework and formulate style transfer as conditional discrete sequence modeling in a learned latent space. Images are decomposed into multi-scale representations and tokenized into discrete codes by a VQ-VAE; a transformer then autoregressively models the distribution of target tokens conditioned on style and content tokens. To inject style and content information, we.