WireForge: Structured Low-Poly Mesh Generation with 2D Wireframe Priors

Low-poly mesh generation is fundamentally underdetermined: the same input shape can be approximated by different polygonal layouts. Existing generators rely on surface conditioning and mesh-connectivity priors learned from the training distribution to select among these layouts, but matching the input geometry does not guarantee that edges follow salient structures. We present WireForge, a framework that addresses this gap by introducing 2D wireframe priors as explicit structural references for generation. These references are constructed by a wireframe-generation agent, WirePilot, built on off-the-shelf image-generation models. Guided by either our carefully designed default instructions or user-provided prompts, the agent generates, evaluates, and refines candidate wireframes. To translate these image-space references into 3D guidance, WireForge associates their features with spatial anchors derived from the input mesh and applies 3D positional encoding. The spatially grounded features then guide mesh generation through cross-attention, complementing geometric guidance from surface samples. This conditioning formulation can be adapted to different mesh-generation backbones, while retaining the wireframe as an editable interface for specifying edge-layout styles through natural-language instructions or sketches. Experiments demonstrate that the resulting structural guidance improves both geometric fidelity and edge-layout alignment.