UnfoldArt: Zero-Shot Recovery of Full Articulated 3D Objects from Text or Image

Mohamed El Amine Boudjoghra¹  ·  Ivan Laptev²  ·  Angela Dai^1
1Technical University of Munich    ²Mohamed Bin Zayed University of Artificial Intelligence

For the full video, see the ▶ video on YouTube or the project page.

Abstract

Articulated 3D objects are essential for interactive environments in embodied AI, robotics, and virtual reality, but reconstructing their structure and motion from sparse observations remains challenging. Existing approaches remain largely constrained by lack of supervised data or lack the priors needed to reliably recover articulation, hidden geometry, and internal object structure.

We present the first debate-driven agentic approach to articulated 3D object reconstruction from text or image inputs that both grounds articulation reasoning in concrete motion and exposes the occluded geometry revealed under articulation. High-level agents reason about object semantics and motion using knowledge from vision-language and video models, while low-level agents estimate articulation parameters and interaction points; together, they engage in a two-round structured debate that first exploits global–local disagreement and then grounds the agents in freely generated video. The same video prior, conditioned on the agreed articulation, then drives each part through its motion to expose occluded interiors and geometry that cannot be inferred from a single static view.

By combining agentic reasoning with a video generative prior, our approach jointly infers articulation and reconstructs complete 3D articulated objects, producing high-fidelity geometry, internal structure, and motion-consistent states beyond directly observed surfaces.

Links

• 🌐 Project page: https://aminebdj.github.io/unfoldart/
• 📄 Paper / arXiv: https://arxiv.org/abs/2606.30608
• ▶️ Video: https://www.youtube.com/watch?v=PBB3jevRhNQ

Code

The code is coming soon. ⭐ Star and watch this repository to be notified when it is released.

Acknowledgements

Our work is built on top of these excellent projects — we thank their authors for open-sourcing their work:

• Wan-VACE
• TRELLIS.2
• SegviGen
• FLUX

Citation

If you find our work useful, please consider citing:

@misc{boudjoghra2026unfoldartzeroshotrecoveryarticulated,
  title={UnfoldArt: Zero-Shot Recovery of Full Articulated 3D Objects from Text or Image},
  author={Mohamed el amine boudjoghra and Ivan Laptev and Angela Dai},
  year={2026},
  eprint={2606.30608},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2606.30608},
}