2022 Fiscal Year Annual Research Report
Explore how to facilitate the human creative process from the perspective of Computer G raphics
| Project/Area Number |
21F20075
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| Research Institution | The University of Tokyo |
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Principal Investigator |
五十嵐 健夫 東京大学, 大学院情報理工学系研究科, 教授 (80345123)
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| Co-Investigator(Kenkyū-buntansha) |
SHEN I-CHAO 東京大学, 情報理工学(系)研究科, 外国人特別研究員
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| Project Period (FY) |
2021-04-28 – 2023-03-31
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| Keywords | コンピューターグラフィックス / 機械学習 |
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| Outline of Annual Research Achievements |
In the past year, I have worked on seven projects and had four papers accepted.
The main theme of these projects is (1) to increase the ability of the generative model by providing user inputs and (2) to assist users in creating ML algorithms. These projects are relevant to edit nerf model and capturing nerf model, image-based shape part manipulation, indoor scene reconstruction from 360 images, and layout generation for graphic design.
In more detail, I introduce the first framework that enables users to remove unwanted objects or retouch undesired regions in a 3D scene represented by a pre-trained NeRF without any category-specific data and training. On the other hand, I proposed a novel containment-aware loss function for layout generation.
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| Research Progress Status |
令和4年度が最終年度であるため、記入しない。
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| Strategy for Future Research Activity |
令和4年度が最終年度であるため、記入しない。
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