Diffusion Probabilistic Models for Scene-Scale 3D Categorical Data

Understand

In this paper, we learn a diffusion model to generate 3D data on a scene-scale.

• Specifically, our model crafts a 3D scene consisting of multiple objects, while recent diffusion research has focused on a single object.
• To realize our goal, we represent a scene with discrete class labels, i.e., categorical distribution, to assign multiple objects into semantic categories.
• Thus, we extend discrete diffusion models to learn scene-scale categorical distributions.