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arXiv · 2509.13688

CraftMesh: High-Fidelity Generative Mesh Manipulation via Poisson Seamless Fusion

James Jincheng·Yuxiao Wu·Youcheng Cai·Ligang Liu
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Abstract

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.

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James Jincheng, Yuxiao Wu, Youcheng Cai, Ligang Liu. 2025-09-17. CraftMesh: High-Fidelity Generative Mesh Manipulation via Poisson Seamless Fusion. https://arxiv.org/abs/2509.13688

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