| 研究実績の概要 |
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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