Controllable, high-fidelity mesh editing remains a significant challenge in 3D content creation. Existing generative methods often struggle with complex geometries and fail to produce detailed results. We propose CraftMesh, a novel framework for high-fidelity generative mesh manipulation via Poisson Seamless Fusion. Our key insight is to decompose mesh editing into a pipeline that leverages the strengths of 2D and 3D generative models: we edit a 2D reference image, then generate a region-specific 3D mesh, and seamlessly fuse it into the original model. We introduce two core techniques: Poisson Geometric Fusion, which utilizes a hybrid SDF/Mesh representation with normal blending to achieve harmonious geometric integration, and Poisson Texture Harmonization for visually consistent texture blending. Experimental results demonstrate that CraftMesh outperforms state-of-the-art methods, delivering superior global consistency and local detail in complex editing tasks.

翻译：可控的高保真网格编辑在三维内容创作中仍面临重大挑战。现有生成方法常难以处理复杂几何结构，且无法生成精细结果。本文提出CraftMesh——一种通过泊松无缝融合实现高保真生成式网格操作的新型框架。我们的核心思路是将网格编辑解构为能融合2D与3D生成模型优势的流程：先编辑二维参考图像，再生成区域特定的三维网格，最后将其无缝融合至原始模型。我们引入两项核心技术：泊松几何融合——采用混合符号距离场/网格表示结合法向混合实现协调的几何整合，以及泊松纹理协调——实现视觉一致的纹理融合。实验结果表明，CraftMesh在复杂编辑任务中优于现有先进方法，在全局一致性与局部细节方面均表现出色。