  3D model reconstruction from a single image has achieved great progress with
the recent deep generative models. However, the conventional reconstruction
approaches with template mesh deformation and implicit fields have difficulty
in reconstructing non-watertight 3D mesh models, such as garments. In contrast
to image-based modeling, the sketch-based approach can help users generate 3D
models to meet the design intentions from hand-drawn sketches. In this study,
we propose Sketch2Cloth, a sketch-based 3D garment generation system using the
unsigned distance fields from the user's sketch input. Sketch2Cloth first
estimates the unsigned distance function of the target 3D model from the sketch
input, and extracts the mesh from the estimated field with Marching Cubes. We
also provide the model editing function to modify the generated mesh. We
verified the proposed Sketch2Cloth with quantitative evaluations on garment
generation and editing with a state-of-the-art approach.
