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AI in Dentistry: Design and create new teeth... VF Net for Dental Point Clouds
Manage episode 444599862 series 3605861
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This paper introduces a new variational autoencoder called VF-Net, specifically designed for dental point clouds. The paper highlights the limitations of existing point cloud models and how VF-Net overcomes them through a novel approach, ensuring a one-to-one correspondence between points in the input and output clouds. The paper also introduces a new dental dataset, FDI 16, which contains a large collection of tooth meshes and point clouds, providing real-world representations for dental research. Through extensive experiments, the paper showcases VF-Net’s superior performance in tasks like point cloud generation, auto-encoding, shape completion, and representation learning. VF-Net demonstrates a significant improvement in reconstruction accuracy and sample realism for dental point clouds compared to existing models. Finally, the paper emphasizes the potential impact of this work in digital dentistry, highlighting the benefits and potential for future research.
Read more: https://arxiv.org/pdf/2307.10895
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