Instruct 3D-to-3D: Text Instruction Guided 3D-to-3D conversion

Hiromichi Kamata, Yuiko Sakuma, Akio Hayakawa, Masato Ishii, Takuya Narihira
3/28/2023
cs.CV

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Abstract

We propose a high-quality 3D-to-3D conversion method, Instruct 3D-to-3D. Our method is designed for a novel task, which is to convert a given 3D scene to another scene according to text instructions. Instruct 3D-to-3D applies pretrained Image-to-Image diffusion models for 3D-to-3D conversion. This enables the likelihood maximization of each viewpoint image and high-quality 3D generation. In addition, our proposed method explicitly inputs the source 3D scene as a condition, which enhances 3D consistency and controllability of how much of the source 3D scene structure is reflected. We also propose dynamic scaling, which allows the intensity of the geometry transformation to be adjusted. We performed quantitative and qualitative evaluations and showed that our proposed method achieves higher quality 3D-to-3D conversions than baseline methods.

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@article{kamata2023instruct,
  title  = {Instruct 3D-to-3D: Text Instruction Guided 3D-to-3D conversion},
  author = {Hiromichi Kamata and Yuiko Sakuma and Akio Hayakawa and Masato Ishii and Takuya Narihira},
  year   = {2023},
  eprint = {2303.15780},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.15780v1}
}

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