Unverified50% confidenceSolutionExact time
Reference-guided Generation is a key technical paradigm in the AI video generation field, in which creators provide character reference images, style samples, or keyframes, and the model extracts style features and combines them with text prompts to generate new video content.
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Long-term
Relevance
9/7/2026
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Unverified参考视频在技术层面充当「结构先验」角色，纹理细节和光照风格由文本提示词和模型自身预训练知识填充74% similarUnverifiedIPAdapter（Image Prompt Adapter）允许用户通过提供参考图像来引导生成图像的风格、构图或主体特征73% similarUnverifiedREF2VA is driven by reference images for generation, guiding video synthesis by extracting visual features from reference frames, and is closer to the image-conditioned generation paradigm.73% similarUnverifiedRepresentative academic works in reference-driven video generation include Animate Anyone, Champ, and MimicMotion, which achieve the separation of identity and motion by introducing dedicated reference encoders (ReferenceNet) or appearance attention mechanisms.72% similarUnverifiedAnimate Anyone (Alibaba, 2023) was the first to systematically introduce ReferenceNet, injecting reference image appearance features into each frame's generation process via cross-frame attention mechanisms.70% similar
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