SIn-NeRF2NeRF: Editing 3D Scenes with Instructions through Segmentation and Inpainting

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Hauptverfasser: Hong, Jiseung, Lee, Changmin, Yu, Gyusang
Format: Preprint
Veröffentlicht: 2024
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author Hong, Jiseung
Lee, Changmin
Yu, Gyusang
author_facet Hong, Jiseung
Lee, Changmin
Yu, Gyusang
contents TL;DR Perform 3D object editing selectively by disentangling it from the background scene. Instruct-NeRF2NeRF (in2n) is a promising method that enables editing of 3D scenes composed of Neural Radiance Field (NeRF) using text prompts. However, it is challenging to perform geometrical modifications such as shrinking, scaling, or moving on both the background and object simultaneously. In this project, we enable geometrical changes of objects within the 3D scene by selectively editing the object after separating it from the scene. We perform object segmentation and background inpainting respectively, and demonstrate various examples of freely resizing or moving disentangled objects within the three-dimensional space.
format Preprint
id arxiv_https___arxiv_org_abs_2408_13285
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle SIn-NeRF2NeRF: Editing 3D Scenes with Instructions through Segmentation and Inpainting
Hong, Jiseung
Lee, Changmin
Yu, Gyusang
Computer Vision and Pattern Recognition
Artificial Intelligence
TL;DR Perform 3D object editing selectively by disentangling it from the background scene. Instruct-NeRF2NeRF (in2n) is a promising method that enables editing of 3D scenes composed of Neural Radiance Field (NeRF) using text prompts. However, it is challenging to perform geometrical modifications such as shrinking, scaling, or moving on both the background and object simultaneously. In this project, we enable geometrical changes of objects within the 3D scene by selectively editing the object after separating it from the scene. We perform object segmentation and background inpainting respectively, and demonstrate various examples of freely resizing or moving disentangled objects within the three-dimensional space.
title SIn-NeRF2NeRF: Editing 3D Scenes with Instructions through Segmentation and Inpainting
topic Computer Vision and Pattern Recognition
Artificial Intelligence
url https://arxiv.org/abs/2408.13285