Single-view indoor scene generation plays a crucial role in a range of real-world applications. However, generating a complete 360° scene from a single image remains a highly ill-posed and challenging problem. Recent approaches have made progress by leveraging diffusion models and depth estimation networks, yet they still struggle to maintain appearance consistency and geometric plausibility under large viewpoint changes, limiting their effectiveness in full-scene generation. To address this, we propose AnchoredDream, a novel zero-shot pipeline that anchors 360° scene generation on high-fidelity geometry via an appearance-geometry mutual boosting mechanism. Given a single-view image, our method first performs appearance-guided geometry generation to construct a reliable 3D scene layout. Then, we progressively generate the complete scene through a series of modules: warp-and-inpaint, warp-and-refine, post-optimization, and a novel Grouting Block, which ensures seamless transitions between the input view and generated regions. Extensive experiments demonstrate that AnchoredDream outperforms existing methods by a large margin in both appearance consistency and geometric plausibility--all in a zero-shot manner. Our results highlight the potential of geometric grounding for high-quality, zero-shot single-view scene generation.

翻译：单视图室内场景生成在众多实际应用中具有关键作用。然而，从单张图像生成完整的360°场景仍是一个高度不适定且极具挑战性的问题。现有方法通过利用扩散模型和深度估计网络已取得进展，但在大视角变化下仍难以保持外观一致性与几何合理性，限制了其在全场景生成中的有效性。为此，我们提出AnchoredDream——一种新颖的零样本流程，通过外观-几何互增强机制将360°场景生成锚定于高保真几何结构之上。给定单视图图像，我们的方法首先执行外观引导的几何生成以构建可靠的三维场景布局；随后通过级联模块逐步生成完整场景：扭曲-修复、扭曲-优化、后优化以及新颖的填缝模块，确保输入视角与生成区域间的无缝过渡。大量实验表明，AnchoredDream在外观一致性与几何合理性方面均显著超越现有方法，且完全以零样本方式实现。我们的研究成果凸显了几何锚定机制在高质量零样本单视图场景生成中的巨大潜力。