MagicCraft: Natural Language-Driven Generation of Dynamic and Interactive 3D Objects for Commercial Metaverse Platforms
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916714543841280 |
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| author | Kurai, Ryutaro Hiraki, Takefumi Hiroi, Yuichi Hirao, Yutaro Perusquía-Hernández, Monica Uchiyama, Hideaki Kiyokawa, Kiyoshi |
| author_facet | Kurai, Ryutaro Hiraki, Takefumi Hiroi, Yuichi Hirao, Yutaro Perusquía-Hernández, Monica Uchiyama, Hideaki Kiyokawa, Kiyoshi |
| contents | Metaverse platforms are rapidly evolving to provide immersive spaces for user interaction and content creation. However, the generation of dynamic and interactive 3D objects remains challenging due to the need for advanced 3D modeling and programming skills. To address this challenge, we present MagicCraft, a system that generates functional 3D objects from natural language prompts for metaverse platforms. MagicCraft uses generative AI models to manage the entire content creation pipeline: converting user text descriptions into images, transforming images into 3D models, predicting object behavior, and assigning necessary attributes and scripts. It also provides an interactive interface for users to refine generated objects by adjusting features such as orientation, scale, seating positions, and grip points.
Implemented on Cluster, a commercial metaverse platform, MagicCraft was evaluated by 7 expert CG designers and 51 general users. Results show that MagicCraft significantly reduces the time and skill required to create 3D objects. Users with no prior experience in 3D modeling or programming successfully created complex, interactive objects and deployed them in the metaverse. Expert feedback highlighted the system's potential to improve content creation workflows and support rapid prototyping. By integrating AI-generated content into metaverse platforms, MagicCraft makes 3D content creation more accessible. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_21332 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MagicCraft: Natural Language-Driven Generation of Dynamic and Interactive 3D Objects for Commercial Metaverse Platforms Kurai, Ryutaro Hiraki, Takefumi Hiroi, Yuichi Hirao, Yutaro Perusquía-Hernández, Monica Uchiyama, Hideaki Kiyokawa, Kiyoshi Human-Computer Interaction Metaverse platforms are rapidly evolving to provide immersive spaces for user interaction and content creation. However, the generation of dynamic and interactive 3D objects remains challenging due to the need for advanced 3D modeling and programming skills. To address this challenge, we present MagicCraft, a system that generates functional 3D objects from natural language prompts for metaverse platforms. MagicCraft uses generative AI models to manage the entire content creation pipeline: converting user text descriptions into images, transforming images into 3D models, predicting object behavior, and assigning necessary attributes and scripts. It also provides an interactive interface for users to refine generated objects by adjusting features such as orientation, scale, seating positions, and grip points. Implemented on Cluster, a commercial metaverse platform, MagicCraft was evaluated by 7 expert CG designers and 51 general users. Results show that MagicCraft significantly reduces the time and skill required to create 3D objects. Users with no prior experience in 3D modeling or programming successfully created complex, interactive objects and deployed them in the metaverse. Expert feedback highlighted the system's potential to improve content creation workflows and support rapid prototyping. By integrating AI-generated content into metaverse platforms, MagicCraft makes 3D content creation more accessible. |
| title | MagicCraft: Natural Language-Driven Generation of Dynamic and Interactive 3D Objects for Commercial Metaverse Platforms |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2504.21332 |