AI RESEARCH
UniCustom: Unified Visual Conditioning for Multi-Reference Image Generation
arXiv CS.CV
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ArXi:2605.12088v1 Announce Type: new Multi-reference image generation aims to synthesize images from textual instructions while faithfully preserving subject identities from multiple reference images. Existing VLM-enhanced diffusion models commonly rely on decoupled visual conditioning: semantic ViT features are processed by the VLM for instruction understanding, whereas appearance-rich VAE features are injected later into the diffusion backbone.