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

arXiv 2603.28152 ↗First posted 30 Mar 2026cs.CVcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 53 of its 61 references that are in the map. First posted on arXiv 30 Mar 2026.

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References · 53

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38 more
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