PrintAnything: Learning Geometric Plan Map for 3D Printing G-code Generation from Unoriented Point Clouds

Point clouds are one of the most fundamental and widelyused 3D representations, serving as the most basic geometric represen-tation of 3D shapes. Nevertheless, most existing 3D printing pipelinesrequire a watertight mesh as input, preventing the direct use of pointclouds for fabrication. A common workaround is to reconstruct meshesfrom point clouds; however, the resulting meshes often contain geomet-ric artifacts, such as incorrect faces or topological inconsistencies, thatare difficult to repair and may lead to printing failures. To overcomethese limitations, we propose PrintAnything, a novel framework thatlearns to produce executable 3D printing G-code directly from 3D pointclouds without requiring mesh reconstruction. To enable point cloudsto serve as direct input for slice-wise toolpath generation, we introducea slice-wise point projection strategy that transforms unstructured 3Dpoint clouds into slice-aligned 2D representations consistent with layer-by-layer nature of fused deposition modeling in 3D printing. To eliminatemesh dependency and provide a unified representation that bridges pointclouds and G-code, we propose Geometric plan (G-plan) map, a com-pact 2D representation composed of occupancy, region, and flow mapsthat encode the geometric and extrusion properties required for toolpathsynthesis in 3D printing. As a result, our proposed method accuratelygenerates printable G-code directly from point clouds, enabling a prac-tical and fully mesh-free pipeline for 3D printing. The code is publiclyavailable at https://github.com/Sangminhong/PrintAnything.