CubePart: 开放词汇部件可控3D生成器

摘要

用于游戏和仿真中的交互式3D资产通常需分解为特定的语义部件，以支持动画、物理和脚本化行为，但目前的多数生成式3D模型输出的要么是单一网格，要么是无法对齐具体应用需求的任意部件分解方案。我们提出CubePart——一个面向开放词汇、部件可控的3D网格生成框架，它将部件结构作为显式的推理时控制信号。给定全局文本提示和用户定义的部件模式（以开放部件名称列表形式表示），我们的方法生成一组网格（每个模式元素对应一个），这些网格在保持指定语义结构的同时组合成一个连贯对象。为实现此功能，我们引入一套可扩展的数据处理流程，以构建大规模的开放词汇部件标注3D数据集，并采用两阶段生成架构，将全局形状合成与部件级解码相分离。我们证明，生成的资产可直接集成至游戏引擎，由动画和行为脚本驱动，无需手动后处理。项目页面：https://cubepart.github.io/

English

Interactive 3D assets used in games and simulation are typically decomposed into specific semantic parts to support animation, physics, and scripted behaviors, yet most generative 3D models produce either monolithic meshes or arbitrary part decompositions that cannot be aligned with application-specific requirements. We present CubePart, a generative framework for open-vocabulary, part-controllable 3D mesh generation that exposes part structure as an explicit inference-time control signal. Given a global text prompt and a user-defined parts schema expressed as an open-ended list of part names, our method generates a set of meshes - one per schema element - that assemble into a coherent object while respecting the specified semantic structure. To enable this capability, we introduce a scalable data pipeline to construct a large open-vocabulary, part-labeled 3D dataset, along with a two-stage generative architecture that separates global shape synthesis from part-level decoding. We demonstrate that the resulting assets can be directly integrated into game engines and driven by animation and behavior scripts without manual post-processing. Project Page: https://cubepart.github.io/