发表机构
Autodesk Research（Autodesk研究院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究针对生成式3D建模中控制有限问题，提出Compos3D系统，通过重新混合部件实现创意控制。用户从提示生成候选，选择部件组装，系统合成模型。用户研究表明该方法能带来更好控制、意图匹配和满意度，还给出了未来工作流程设计建议。
AI 中文摘要
虽然生成式人工智能为3D内容创作带来了新机遇，但当前工作流程常依赖多次重新生成，控制有限且结果不可预测。我们提出Compos3D系统，通过重新混合为生成式3D建模引入合成工作流程。用户从文本或图像提示生成多个候选，通过2D图像区域或3D网格段选择感兴趣部分并组装成连贯设计。系统将这些合成物合成精细3D模型，保留高层意图并解决底层几何问题。我们进行了用户研究比较2D和3D模态下的重新混合与重新生成工作流程。结果表明重新混合工作流程为参与者提供了更大创意控制、与意图更强的一致性和更高满意度。我们最后给出了未来人工智能辅助3D建模工作流程的设计建议。
英文摘要
While generative AI has unlocked new opportunities for 3D content creation, current workflows often rely on multiple regenerations, which provides limited control and unpredictable outcomes. We present Compos3D, a system that introduces a compositional workflow for generative 3D modeling through remixing. Instead of repeatedly regenerating models, users generate multiple candidates from text or image prompts, select parts of interest via 2D image regions or 3D mesh segments, and assemble them into a coherent design. The system synthesizes these compositions into a refined 3D model, preserving high-level intent while resolving low-level geometry. To evaluate this approach, we conducted a controlled user study comparing remixing and regeneration workflows across both 2D and 3D modalities. Results show that the remixing workflow provides participants with greater creative control, stronger alignment with their intent, and higher satisfaction. We conclude with design recommendations for future AI-assisted 3D modeling workflows.
