StateFlow：面向预可视化的三维世界状态构建、演化与访问

摘要

预可视化是电影、游戏、建筑和城市设计中连接创意与制作之间的中间层，使创作者能够迭代式地打磨场景、动作、相机以及时空动态。然而，现有生成方法仅依赖简单提示词，通过一次性图像或视频合成来联合控制所有这些因素，导致可控性弱且对迭代式编辑的支持有限。从根本上说，一个世界由多个具有几何、外观及其他属性的元素以及相机共同组成，不同帧通过对这一共享状态进行局部修改或重新组合而生成，而该状态在其余情况下基本被复用。因此，我们认为所缺失的组件是一个显式的、持久的工作状态。为解决这一问题，我们提出StateFlow，一种以状态为中心的生成式预可视化框架。StateFlow并非一次性生成视频，而是利用一个可编辑的3D世界来组织场景结构、演化过程及相机配置，同时在需要更高保真度时借助现成的视频模型来增强视觉质量。这个世界以场景元素与相机配置的持久化结构化3D状态形式得以维护，作为预可视化的核心工作表示。基于这一洞察，StateFlow包含三个阶段来构建、演化并访问世界状态。状态构建通过先验引导的、冲突感知的双视图初始化，将生成的2D内容提升为连贯的3D世界；状态演化则在保留世界记忆的同时，将用户意图转化为结构化的状态转换，避免每次编辑都触发全场景重新生成；状态访问利用渲染反馈反思将相机规划精炼为视觉上可行的轨迹，避免仅依赖视觉语言模型的语义判断。实验表明，StateFlow能够为视频创作和类游戏原型设计生成高质量的3D世界。

English

Previsualization is an intermediate layer between ideas and production in film, games, architecture, and urban design. It lets creators iteratively refine scenes, actions, cameras, and spatial-temporal dynamics. Yet existing generative methods rely on simple prompts to jointly control all of these factors through one-shot image or video synthesis, offering weak controllability and limited support for iterative editing. Fundamentally, a world comprises multiple elements with geometry, appearance, and other attributes, together with cameras. Different frames are produced through local modifications or recombinations of this shared state, which is otherwise largely reused. Therefore, we argue that the missing component is an explicit and persistent working state. To address this, we present StateFlow, a state-centric framework for generative previsualization. Rather than generating videos in one shot, StateFlow 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. This world is maintained as a persistent structured 3D state of scene elements and camera configurations, serving as the core working representation for previsualization. Built on this insight, StateFlow has three stages to construct, evolve, and access the world state. State construction lifts generated 2D content into a coherent 3D world through prior-guided, conflict-aware dual-view initialization, while State evolution translates user intent into structured state transitions while preserving world memory, avoiding full-scene regeneration for each edit. State access uses render-feedback reflection to refine camera plans into visually feasible trajectories, avoiding reliance on VLM semantics alone. Experiments show that StateFlow produces high-quality 3D worlds for video creation and game-like prototyping.