Chat-Edit-3D: Interactive 3D Scene Editing via Text Prompts

Fuente: arXiv
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Main Authors: Fang, Shuangkang, Wang, Yufeng, Tsai, Yi-Hsuan, Yang, Yi, Ding, Wenrui, Zhou, Shuchang, Yang, Ming-Hsuan
Format: Preprint
Published: 2024
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author Fang, Shuangkang
Wang, Yufeng
Tsai, Yi-Hsuan
Yang, Yi
Ding, Wenrui
Zhou, Shuchang
Yang, Ming-Hsuan
author_facet Fang, Shuangkang
Wang, Yufeng
Tsai, Yi-Hsuan
Yang, Yi
Ding, Wenrui
Zhou, Shuchang
Yang, Ming-Hsuan
contents Recent work on image content manipulation based on vision-language pre-training models has been effectively extended to text-driven 3D scene editing. However, existing schemes for 3D scene editing still exhibit certain shortcomings, hindering their further interactive design. Such schemes typically adhere to fixed input patterns, limiting users' flexibility in text input. Moreover, their editing capabilities are constrained by a single or a few 2D visual models and require intricate pipeline design to integrate these models into 3D reconstruction processes. To address the aforementioned issues, we propose a dialogue-based 3D scene editing approach, termed CE3D, which is centered around a large language model that allows for arbitrary textual input from users and interprets their intentions, subsequently facilitating the autonomous invocation of the corresponding visual expert models. Furthermore, we design a scheme utilizing Hash-Atlas to represent 3D scene views, which transfers the editing of 3D scenes onto 2D atlas images. This design achieves complete decoupling between the 2D editing and 3D reconstruction processes, enabling CE3D to flexibly integrate a wide range of existing 2D or 3D visual models without necessitating intricate fusion designs. Experimental results demonstrate that CE3D effectively integrates multiple visual models to achieve diverse editing visual effects, possessing strong scene comprehension and multi-round dialog capabilities. The code is available at https://sk-fun.fun/CE3D.
format Preprint
id arxiv_https___arxiv_org_abs_2407_06842
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Chat-Edit-3D: Interactive 3D Scene Editing via Text Prompts
Fang, Shuangkang
Wang, Yufeng
Tsai, Yi-Hsuan
Yang, Yi
Ding, Wenrui
Zhou, Shuchang
Yang, Ming-Hsuan
Computer Vision and Pattern Recognition
Recent work on image content manipulation based on vision-language pre-training models has been effectively extended to text-driven 3D scene editing. However, existing schemes for 3D scene editing still exhibit certain shortcomings, hindering their further interactive design. Such schemes typically adhere to fixed input patterns, limiting users' flexibility in text input. Moreover, their editing capabilities are constrained by a single or a few 2D visual models and require intricate pipeline design to integrate these models into 3D reconstruction processes. To address the aforementioned issues, we propose a dialogue-based 3D scene editing approach, termed CE3D, which is centered around a large language model that allows for arbitrary textual input from users and interprets their intentions, subsequently facilitating the autonomous invocation of the corresponding visual expert models. Furthermore, we design a scheme utilizing Hash-Atlas to represent 3D scene views, which transfers the editing of 3D scenes onto 2D atlas images. This design achieves complete decoupling between the 2D editing and 3D reconstruction processes, enabling CE3D to flexibly integrate a wide range of existing 2D or 3D visual models without necessitating intricate fusion designs. Experimental results demonstrate that CE3D effectively integrates multiple visual models to achieve diverse editing visual effects, possessing strong scene comprehension and multi-round dialog capabilities. The code is available at https://sk-fun.fun/CE3D.
title Chat-Edit-3D: Interactive 3D Scene Editing via Text Prompts
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2407.06842