MVDream

Multi-view conditioning: Generates consistent multi-view images by conditioning the diffusion model on camera viewpoint alongside the text prompt.

2D diffusion + 3D data: Leverages pretrained 2D diffusion models and a multi-view dataset rendered from 3D assets, combining 2D generalizability with 3D consistency.

Best of both worlds: Inherits the creativity of 2D diffusion priors while maintaining the geometric coherence required for downstream 3D reconstruction.

3D generation foundation: Became a building block for many subsequent text-to-3D pipelines that rely on multi-view-consistent diffusion as a prior.