ObjectMorpher: 3D-Aware Image Editing via Deformable 3DGS Models

CVPR 2026
Yuhuan Xie*,
Aoxuan Pan*,
Yi-Hua Huang†,
Chirui Chang ,
Peng Dai ,
Xin Yu ,
Xiaojuan Qi#

The University of Hong Kong,
*Equal Contribution, †Project Leader, #Corresponding Author
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Paper arXiv Code
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Abstract

Achieving precise, object-level control in image editing remains challenging: 2D methods lack 3D awareness and often yield ambiguous or implausible results, while existing 3D-aware approaches rely on heavy optimization or incomplete monocular reconstructions. We present ObjectMorpher, a unified, interactive framework that converts ambiguous 2D edits into geometry-grounded operations. ObjectMorpher lifts target instances with an image-to-3D generator into editable 3D Gaussian Splatting (3DGS), enabling fast, identity-preserving manipulation. Users drag control points; a graph-based non-rigid deformation with as-rigid-as-possible (ARAP) constraints ensures physically sensible shape and pose changes. A composite diffusion module harmonizes lighting, color, and boundaries for seamless reintegration. Across diverse categories, ObjectMorpher delivers fine-grained, photorealistic edits with superior controllability and efficiency, outperforming 2D drag and 3D-aware baselines on KID, LPIPS, SIFID, and user preference.

Pipeline

The object is lifted from 2D pixels to high-fidelity 3DGS. Real-time editing with local rigidity is applied based on user input. The object is then repositioned, and a generative model refines the edits for harmonious results.

pipeline

Interactive Editing

Results

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BibTeX

@misc{xie2026objectmorpher3dawareimageediting,
      title={ObjectMorpher: 3D-Aware Image Editing via Deformable 3DGS Models}, 
      author={Yuhuan Xie and Aoxuan Pan and Yi-Hua Huang and Chirui Chang and Peng Dai and Xin Yu and Xiaojuan Qi},
      year={2026},
      eprint={2603.28152},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2603.28152}, 
}