We present Multimodal Flow, a fully continuous generative model of language and vision. Most unified multimodal models either model both language and quantized images as discrete tokens or combine discrete language prediction with continuous image generation. The former introduces a visual quantization bottleneck. The...
Hong-Yuan Tao, Xing-Gang Wang, Liang-Hui Zhu et al.· 0 citations
StructGen is proposed, which employs a structured, dictionary-like format to encode multiple reference images, thereby enabling explicit and unambiguous specification of generation intentions, and consistently outperforms existing methods on both semantic alignment and detailed reference-generation consistency.
StateFlow is presented, a state-centric framework for generative previsualization that uses an editable 3D world to organize scene structure, evolution, and cameras, while off-the-shelf video models enhance visual quality when higher fidelity is desired.
Yuyang Yin, Zixiang Li, Longxiulin Deng et al.· 1 citation
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