让3D生成可分部件、可编辑,还能保持结构完整。
OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion
- 先用2D掩码规划部件布局,再统一生成各部分
- 生成的部件间语义清晰分离,整体结构稳固
- 适合需要精细控制3D模型的应用场景
生成具有明确可编辑部件结构的3D资产对交互应用至关重要,但现有生成方法大多产出单一整体形状,限制了实用性。我们提出OmniPart,一种面向部件感知的3D生成框架,旨在实现组件间高语义解耦的同时保持强结构连贯性。OmniPart将该复杂任务分解为两个协同阶段:(1) 自回归结构规划模块生成可控制、可变长度的3D部件边界框序列,由灵活的2D部件掩码引导,实现无需对应关系或语义标签的直观部件分解;(2) 基于预训练整体3D生成器高效适配的空间条件修正流模型,同步且一致地在规划布局内合成所有3D部件。本方法支持用户定义的部件粒度与精确定位,适用于多样下游任务。大量实验表明,OmniPart达到当前最优性能,为更可解释、可编辑、多功能的3D内容生成铺平道路。
原文摘要 · Abstract (English)
The creation of 3D assets with explicit, editable part structures is crucial for advancing interactive applications, yet most generative methods produce only monolithic shapes, limiting their utility. We introduce OmniPart, a novel framework for part-aware 3D object generation designed to achieve high semantic decoupling among components while maintaining robust structural cohesion. OmniPart uniquely decouples this complex task into two synergistic stages: (1) an autoregressive structure planning module generates a controllable, variable-length sequence of 3D part bounding boxes, critically guided by flexible 2D part masks that allow for intuitive control over part decomposition without requiring direct correspondences or semantic labels; and (2) a spatially-conditioned rectified flow model, efficiently adapted from a pre-trained holistic 3D generator, synthesizes all 3D parts simultaneously and consistently within the planned layout. Our approach supports user-defined part granularity, precise localization, and enables diverse downstream applications. Extensive experiments demonstrate that OmniPart achieves state-of-the-art performance, paving the way for more interpretable, editable, and versatile 3D content.
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