I am one of the authors, Nobuyuki Umetani from the University of Tokyo, who implemented all the codes. I am delighted to see so many good discussions here!
I fully understand that the quality of the result is low for the architectural standard. This research does not mean computing a perfect floor plan ready for architectural design. It's more like it gives the architect some rough design choices in the very early design stage.
This research presents a new shape representation (differentiable Voronoi) for solving layout problems. These challenging problems typically involve geometrical and topological constraints. Existing shape representations are classified mainly into explicit (mesh) and implicit (using an implicit function) representations. While mesh representation is challenging in handling topological change, implicit representation is problematic because the boundary is not explicitly defined. Thus, it is difficult to compute the loss function based on the boundary shape. Differential Voronoi representation has both implicit and explicit representation properties (the wall is defined explicitly while the distance function from sites determines the shape) and is suitable for optimizing geometry and topology together.
Thank you! I am happy that our research reaches such a large audience!!
I fully understand that the quality of the result is low for the architectural standard. This research does not mean computing a perfect floor plan ready for architectural design. It's more like it gives the architect some rough design choices in the very early design stage.
This research presents a new shape representation (differentiable Voronoi) for solving layout problems. These challenging problems typically involve geometrical and topological constraints. Existing shape representations are classified mainly into explicit (mesh) and implicit (using an implicit function) representations. While mesh representation is challenging in handling topological change, implicit representation is problematic because the boundary is not explicitly defined. Thus, it is difficult to compute the loss function based on the boundary shape. Differential Voronoi representation has both implicit and explicit representation properties (the wall is defined explicitly while the distance function from sites determines the shape) and is suitable for optimizing geometry and topology together.
Thank you! I am happy that our research reaches such a large audience!!
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