7 citations · 11 across the 2 of their papers we have counts for
2 papers
cs.CV2023★ 4 cited
Learning Self-Prior for Mesh Inpainting Using Self-Supervised Graph Convolutional Networks
Shota Hattori, Tatsuya Yatagawa, Yutaka Ohtake +1
In this paper, we present a self-prior-based mesh inpainting framework that requires only an incomplete mesh as input, without the need for any training datasets. Additionally, our…
cs.CV2021★ 7 cited
Deep Mesh Prior: Unsupervised Mesh Restoration using Graph Convolutional Networks
Shota Hattori, Tatsuya Yatagawa, Yutaka Ohtake +1
This paper addresses mesh restoration problems, i.e., denoising and completion, by learning self-similarity in an unsupervised manner. For this purpose, the proposed method, which…