MultiCube: Compositional 3D Generation With Part-Level Semantic and Spatial Control

2026-08-20

AI Summary

为解决3D对象生成中缺乏部件级精确控制的问题，MultiCube通过两阶段扩散过程和独立部件条件编码方法实现对各部分语义及空间布局的精细控制。

Abstract

Digital 3D objects used in games and animation are often required to be compositional; that is, decomposed into semantically meaningful parts. Recent 3D generation methods can produce high-quality compositional objects conditioned on image or text prompts. Yet, such global conditioning lacks the precise part-level controllability required for professional creative workflows. To address this, we introduce MultiCube, a novel compositional 3D generation method that provides explicit, independent control over both the semantics and spatial arrangement of each part. MultiCube takes as input a global text prompt, a text schema specifying the desired parts, and a spatial layout indicating the bounding boxes of the parts in the given schema. It outputs a 3D object composed of distinct meshes, one per specified part, that adhere to the given semantic and spatial conditions. Our approach employs a two-stage diffusion process, first generating a schema- and layout-aligned monolithic mesh, then decomposing the mesh into individual parts simultaneously. A novel Part Layout Adapter is used to encode per-part conditions independently of the other parts. Experiments demonstrate that our method can generate high-quality compositional 3D objects with precise part-level control, including those with unique layouts difficult to achieve with text or image prompting alone. Project page: https://multi-cube.github.io

Problem

• Compositional 3D Generation
• Part-Level Control
• Semantic and Spatial Control

Innovation

• compositional 3D generation
• part-level control
• two-stage diffusion process
• Part Layout Adapter