一张照片，AI 把世界写成代码，还能递归拆解重建
现在的 AI 从一张照片重建 3D 场景，大多是整体糊一层，细节一放大就崩。这篇换了个思路：把世界当成一段可执行的程序，而且这段程序会递归地调用自己——先搭全局，再钻进没建好的局部单独重建，最后跳出来重新审视整体、修补接缝和关系。每一层细节都有自己的感知和编辑循环，但所有层级共用同一套相机投影，所以局部修完不会把全局搞歪。研究者用视觉语言模型直接对比参考图和渲染结果来指导这个递归过程，在复杂场景上超过了此前的代码式重建方法。它不是你明天能用的工具，但「递归地拆解世界」这个原则，可能是让 AI 从一张图里长出完整、精细 3D 世界的下一步。
📄 原文摘要(英文)
Code world models represent worlds as executable programs, but this representation alone does not determine how to construct a complex world. We introduce Recursive Code World Models (RCWM), a framework for reconstructing complex 3D worlds in code from a single reference image. RCWM couples a Recursive Scene Program (RSP) representation with a construction solver that recursively calls itself. An RSP represents the executable world as compositional scene code, while each solver call follows the same complete process: establish the whole, recursively reconstruct unresolved parts, and revisit the whole to refine their composition. This global-local-global recursion gives fine-scale structures their own perception-and-editing loops while preserving scene-wide geometry and relationships. Reference-aligned views propagate a shared camera projection across levels, while parent revisitation addresses boundaries, spatial relations, and shared errors that emerge after local refinement. A vision-language coding agent directly compares reference images with scene renders to guide refinement, recursive descent, and return. Across complex scenes, RCWM outperforms prior code-based image-to-scene reconstruction methods. Ablation studies further support the benefits of recursive construction and suggest that deeper calls can improve finer-scale reconstruction. RCWM provides a recursive construction principle for building complex executable worlds from visual evidence.