We propose a method for editing 3D Gaussian Splatting (3DGS) scenes with text-instructions. Given a 3DGS scene 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 realistic and targeted edits.

Our method gradually updates a reconstructed 3DGS scene by iteratively updating the dataset images while training the 3DGS:

1. Images are rendered from the scene at training viewpoints.
2. They get edited by InstructPix2Pix given a global text instruction.
3. The training dataset images are replaced with the edited images.
4. The 3DGS continues training as usual for 2.5k iterations.