PrITTI: Primitive-based Generation of Controllable and Editable 3D Semantic Urban Scenes

Understand

Existing approaches to 3D semantic urban scene generation predominantly rely on voxel-based representations, which are bound by fixed resolution, challenging to edit, and memory-intensive in their dense form.

• In contrast, we advocate for a primitive-based paradigm where urban scenes are represented using compact, semantically meaningful 3D elements that are easy to manipulate and compose.
• To this end, we introduce PrITTI, a latent diffusion model that leverages vectorized object primitives and rasterized ground surfaces for generating diverse, controllable, and editable 3D semantic urban scenes.
• This hybrid representation yields a structured latent space that facilitates object- and ground-level manipulation.