Text-To-4D is a new method developed by Meta for generates 3D dynamic scenes from text descriptions. It uses a 4D dynamic Neural Radiance Field (NeRF) that is optimized for scene appearance, density, and motion consistency by querying a Text-to-Video (T2V) diffusion-based model.
Generates 3D dynamic scenes from text
Generates 3D dynamic scenes from text descriptions
Uses a 4D dynamic Neural Radiance Field (NeRF)
Optimizes for scene appearance, density, and motion consistency
Queries a Text-to-Video (T2V) diffusion-based model
Does not require any 3D or 4D data
T2V model is trained only on Text-Image pairs and unlabeled videos
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