Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields

Understand

Text-driven 3D scene generation is widely applicable to video gaming, film industry, and metaverse applications that have a large demand for 3D scenes.

• However, existing text-to-3D generation methods are limited to producing 3D objects with simple geometries and dreamlike styles that lack realism.
• In this work, we present Text2NeRF, which is able to generate a wide range of 3D scenes with complicated geometric structures and high-fidelity textures purely from a text prompt.
• To this end, we adopt NeRF as the 3D representation and leverage a pre-trained text-to-image diffusion model to constrain the 3D reconstruction of the NeRF to reflect the scene description.