PartCrafter: One‑Shot Structured 3D Mesh Generation from a Single Image

Imagine uploading a single RGB image and instantly receiving a full 3D model broken down into individual, semantically meaningful parts, ready for editing, printing, or animation. That’s exactly what PartCrafter accomplishes.

Paper & Repository

Research Paper
Title: “PartCrafter: Structured 3D Mesh Generation via Compositional Latent Diffusion Transformers”
Authors: Yuchen Lin, Chenguo Lin, Panwang Pan, Honglei Yan, Yiqiang Feng, Yadong Mu, Katerina Fragkiadaki
Published: June 5, 2025, on arXiv

Official GitHub Repository

• Contains full code, with MIT license, and will release model weights + demos by mid-July

Project Page

• Hosted by the authors, summarizing the method and linking to paper and code

  
  

Key Highlights

One‑Shot Multi-Part Generation: From a single RGB image, the model generates multiple 3D mesh parts simultaneously, no segmentation needed first.

• Compositional Latent Space: Each part corresponds to a distinct set of latent tokens, plus a learned identity embedding.

• Hierarchical Attention: A dual attention mechanism maintains detail within parts and coherence across the entire object.

• Pretrained 3D Mesh Diffusion Transformer (DiT): Leverages pretrained DiT components for faster convergence and higher fidelity.

  
  

Performance & Dataset

Dataset: Curated ~130,000 objects with part annotations extracted from Objaverse, ShapeNet, ABO with about 300,000 parts.

• Speed: Generates full part-aware mesh in ~30–34 seconds on a GPU, outperforming older two-stage pipelines (~18 minutes).

• Quality: Achieves lower Chamfer distance and higher F-score (F ≈ 0.7472) than HoloPart and baseline DiT methods

  
  

Use Cases

3D Printing: Creates individual STL-ready parts for easy assembly (Tom’s Hardware feature).

• CAD & Design: Enables part-level editing and modular asset creation.

• AR/VR & Games: Facilitates generation of decomposable assets directly from reference images.

• Robotics & Simulation: Provides structural understanding for object manipulation.

  
  

What's Available Now

Code & Checkpoints: Public GitHub repo available now. Model weights and demo expected before July 15, 2025.

• Technical Demo: Live demonstrations and project page visuals show input-to-mesh workflow .

  
  

https://github.com/wgsxm/PartCrafter

https://arxiv.org/abs/2506.05573