“GaussianCube: Structuring Gaussian Splatting using Optimal Transport for 3D Generative Modeling” details an innovative method that refines 3D Gaussian Splatting for enhanced 3D fitting fidelity and rendering speed.

• Proposes a modified densification-constrained GS fitting algorithm to allow for structured GS representation.
• Re-arranges the Gaussians into a predefined voxel grid using Optimal Transport.
• Adopts a 3D U-Net backbone in diffusion generative modeling to make use of the new structured representation.
• Demonstrates exceptional generation results through comprehensive experiments on diverse 3D datasets.

This exploration strengthens the capability for 3D modeling and offers insights into the power of structured representations in generative AI, marking a significant evolution of 3D modeling techniques.