Instruct-NeRF2NeRF: Editing 3D Scenes with Instructions

Autor:	Haque, Ayaan, Tancik, Matthew, Efros, Alexei A., Holynski, Aleksander, Kanazawa, Angjoo
Rok vydání:	2023
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Graphics
Druh dokumentu:	Working Paper
Popis:	We propose a method for editing NeRF scenes with text-instructions. Given a NeRF of a scene and the collection of images used to reconstruct it, our method uses an image-conditioned diffusion model (InstructPix2Pix) to iteratively edit the input images while optimizing the underlying scene, resulting in an optimized 3D scene that respects the edit instruction. We demonstrate that our proposed method is able to edit large-scale, real-world scenes, and is able to accomplish more realistic, targeted edits than prior work. Comment: Project website: https://instruct-nerf2nerf.github.io; v1. Revisions to related work and discussion
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2303.12789 Zobrazit plný text záznamu View this record from Arxiv