CraftMesh: High-Fidelity Generative Mesh Manipulation via Poisson Seamless Fusion
This addresses the problem of controllable, high-fidelity mesh editing for 3D content creators, representing a novel method for a known bottleneck.
The paper tackles the challenge of high-fidelity mesh editing in 3D content creation by proposing CraftMesh, a framework that decomposes editing into a pipeline using 2D and 3D generative models with Poisson Seamless Fusion, resulting in superior global consistency and local detail compared to state-of-the-art methods.
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.