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Found 3 papers, 2 papers with code
Learning Self-Prior for Mesh Inpainting Using Self-Supervised Graph Convolutional Networks
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.
Deep Point-to-Plane Registration by Efficient Backpropagation for Error Minimizing Function
To solve this problem, we consider the estimated rigid transformation as a function of input point clouds and derive its analytic gradients using the implicit function theorem.
Deep Mesh Prior: Unsupervised Mesh Restoration using Graph Convolutional Networks
This paper addresses mesh restoration problems, i. e., denoising and completion, by learning self-similarity in an unsupervised manner.
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