DATENeRF: Depth-Aware Text-based Editing of NeRFs

arXiv:2404.04526v1 Announce Type: new
Abstract: Recent advancements in diffusion models have shown remarkable proficiency in editing 2D images based on text prompts. However, extending these techniques to edit scenes in Neural Radiance Fields (NeRF) is complex, as editing individual 2D frames can result in inconsistencies across multiple views. Our crucial insight is that a NeRF scene's geometry can serve as a bridge to integrate these 2D edits. Utilizing this geometry, we employ a depth-conditioned ControlNet to enhance the coherence of …

abstract arxiv cs.cv diffusion diffusion models edit editing fields however images insight multiple nerf neural radiance fields prompts text type