From One to More: Contextual Part Latents for 3D Generation
Shaocong Dong, Lihe Ding, Xiao Chen, Yaokun Li, Yuxin Wang, Yucheng Wang, Qi Wang, Jaehyeok Kim, Chenjian Gao, Zhanpeng Huang, Zibin Wang, Tianfan Xue, Dan Xu
2025-07-14
Summary
This paper talks about CoPart, a new method for generating 3D objects that breaks down objects into parts and looks at how these parts relate to each other during the creation process.
What's the problem?
Creating detailed and realistic 3D objects is challenging because current methods often treat the object as a whole without understanding the different parts and how they connect, leading to less control and less detailed results.
What's the solution?
The researchers designed a system that splits 3D objects into separate parts called part latents and models these parts with their context, so the AI can generate objects with better details, clearer relationships between parts, and more control over how the parts come together.
Why it matters?
This matters because it makes 3D generation more accurate and flexible, helping artists and designers create complex objects more easily and improving applications like gaming, animation, and virtual reality.
Abstract
CoPart, a part-aware diffusion framework, enhances 3D generation by decomposing objects into contextual part latents, improving detail, part relationships, and controllability.