NeuralGF: Unsupervised Point Normal Estimation by Learning Neural Gradient Function -- Supplementary Material -- Qing Li

Neural Information Processing Systems 

We provide optimization time ( i. e ., training time in the bracket) and inference time of our method. Our method improves the state-of-the-art results while using much fewer parameters. The surfaces are reconstructed from point clouds with low noise (a) and high noise (b). Fig 2, we show the reconstructed surfaces on point clouds with different noise levels. A partially enlarged view is provided for each shape.

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