ObjectMorpher: 通过可变形3DGS模型实现3D感知的图像编辑
ObjectMorpher: 3D-Aware Image Editing via Deformable 3DGS Models
AI总结：
ObjectMorpher通过可变形3DGS模型实现3D感知图像编辑，提供精确的物体级控制，支持快速且保持身份的编辑，优于2D拖拽和3D感知基线。
摘要：
实现精确的物体级图像编辑仍具挑战性：2D方法缺乏3D意识，常产生模糊或不合理的结果，而现有3D感知方法依赖重优化或不完整的单目重建。我们提出ObjectMorpher，一个统一的交互框架，将模糊的2D编辑转换为基于几何的操作。ObjectMorpher通过图像到3D生成器提升目标实例，使其成为可编辑的3D高斯点散列（3DGS），实现快速且保持身份的操控。用户拖动控制点；基于图的非刚性变形结合尽可能刚性的（ARAP）约束，确保物理合理的形状和姿态变化。复合扩散模块协调光照、颜色和边界，实现无缝再整合。在多样类别中，ObjectMorpher提供精细的、逼真的编辑，具有更优的可控性和效率，在KID、LPIPS、SIFID和用户偏好上优于2D拖拽和3D感知基线。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
