2

Fig. 1. We propose Text2NeRF, a text-driven 3D scene generation framework by combining the neural radiance ﬁeld representation and a pre-trained
text-to-image diffusion model. Our Text2NeRF is capable of generating diverse and view-consistent indoor/outdoor 3D scenes solely from natural language
descriptions. Please refer to our supplementary video demo for more examples.

view-consistent 3D scene. In practice, we ﬁnd that single-
view training in NeRF leads to overﬁtting to this view and thus
causes geometric ambiguity during view-by-view updating due
to the lack of multi-view constraints. To overcome this issue,
we build a support set for the generated view to offer multi-
view constraints for the NeRF model.
Text2NeRF- Text-Driven 3D Scene Generation with Neural Radiance Fields