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Existing 3D model reconstruction methods typically produce outputs in theform of voxels, point clouds, or meshes. However, each of these approaches hasits limitations and may not be suitable for every scenario. For instance, theresulting model may exhibit a rough surface and distorted structure, makingmanual editing and post-processing challenging for humans. In this paper, weintroduce a novel 3D reconstruction method designed to address these issues. Wetrained a visual transformer to predict a "scene descriptor" from a singlewire-frame image. This descriptor encompasses crucial information, includingobject types and parameters such as position, rotation, and size. With thepredicted parameters, a 3D scene can be reconstructed using 3D modelingsoftware like Blender or Rhino Grasshopper which provides a programmableinterface, resulting in finely and easily editable 3D models. To evaluate theproposed model, we created two datasets: one featuring simple scenes andanother with complex scenes. The test results demonstrate the model's abilityto accurately reconstruct simple scenes but reveal its challenges with morecomplex ones.

Sketch2CADScript: 3D Scene Reconstruction from 2D Sketch using Visual Transformer and Rhino Grasshopper