SpaceControl: Introducing Test-Time Spatial Control to 3D Generative Modeling

ICLR 2026 Conference Submission20104 Authors

Keywords: 3D Vision, 3D Generative Models, Geometric Primitives

Abstract:

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 cumbersome to edit. In this work, we introduce SpaceControl, a training-free test-time method for explicit spatial control of 3D generation. Our approach accepts diverse geometric inputs, from coarse primitives to detailed meshes, and conditions a powerful pre-trained generative model without additional training. A controllable 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 user interface that enables online editing of superquadrics for direct conversion into textured 3D assets, facilitating practical deployment in creative workflows.

Primary Area: applications to computer vision, audio, language, and other modalities

Submission Number: 20104