Generative methods for 3D assets have recently achieved remarkable progress, yet providing intuitive and precise control over the object geometry remains a key challenge. Existing approaches predominantly rely on text or image prompts, which often fall short in geometric specificity: language can be ambiguous, and images are difficult to manipulate. In this work, we introduce SpaceControl, a training-free test-time method for explicit spatial control of 3D asset generation. Our approach accepts a wide range of geometric inputs, from coarse primitives to detailed meshes, and integrates seamlessly with modern generative models without requiring any additional training. A control parameter lets users trade off between geometric fidelity and output realism. Extensive quantitative evaluation and user studies demonstrate that SpaceControl outperforms both training-based and optimization-based baselines in geometric faithfulness while preserving high visual quality. Finally, we present an interactive interface for real-time superquadric editing and direct 3D asset generation, enabling seamless use in creative workflows. Project page: https://spacecontrol3d.github.io/.

翻译：三维资产的生成方法近年来取得了显著进展，然而，如何对物体几何形状提供直观且精确的控制仍然是一个关键挑战。现有方法主要依赖于文本或图像提示，这些方式通常在几何特异性上有所不足：语言描述可能具有模糊性，而图像则难以精确操控。在本工作中，我们提出了SpaceControl，一种无需训练、可在测试时实现三维资产生成显式空间控制的方法。我们的方法能够接受广泛的几何输入，从粗糙的几何基元到精细的网格，并且无需任何额外训练即可与现代生成模型无缝集成。通过一个控制参数，用户可以在几何保真度与输出真实感之间进行权衡。大量的定量评估和用户研究表明，SpaceControl在保持高视觉质量的同时，其几何忠实度优于基于训练和基于优化的基线方法。最后，我们展示了一个用于实时超二次曲面编辑和直接三维资产生成的交互式界面，使其能够无缝融入创意工作流程。项目页面：https://spacecontrol3d.github.io/。