OmniPart: Part-Aware 3D Generation with Semantic Decoupling and
  Structural Cohesion
Authors: name: Yunhan Yang, name: Yufan Zhou, name: Yuan-Chen Guo, name: Zi-Xin Zou, name: Yukun Huang, name: Ying-Tian Liu, name: Hao Xu, name: Ding Liang, name: Yan-Pei Cao, name: Xihui Liu

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.