Placing Any Object at Any 3D Position

Authors

  • Junhao Zhang Zhejiang University
  • Ming Kong Zhejiang University
  • Zhanbin Hu Beijing Information Science and Technology University
  • Hao Qin Zhejiang University
  • Zhijie Xu University of Michigan - Ann Arbor
  • Xiaojun Zhu Zhejiang University
  • Qiang Zhu Zhejiang University

DOI:

https://doi.org/10.1609/aaai.v40i48.42400

Abstract

In this work, we propose a diffusion-based method for 3D-aware image composition. Previous approaches have focused on 2D-view image composition, which limits their handling of complex 3D spatial relationships. Consequently, they are not well-suited for applications requiring precise 3D object control and iterative refinement, including interior design visualization, visual effects prototyping, and virtual reality scene construction. In contrast, our method extracts 3D bounding boxes for all objects in the scene image. Users can then specify a new 3D bounding box based on existing spatial context and provide an image of the target object. Leveraging a fine-tuned diffusion model, our approach enables high-fidelity image composition while preserving the underlying 3D structure of the scene.

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Published

2026-03-14

How to Cite

Zhang, J., Kong, M., Hu, Z., Qin, H., Xu, Z., Zhu, X., & Zhu, Q. (2026). Placing Any Object at Any 3D Position. Proceedings of the AAAI Conference on Artificial Intelligence, 40(48), 41742–41744. https://doi.org/10.1609/aaai.v40i48.42400