ma-xu / pointMLP-pytorch

[ICLR 2022 poster] Official PyTorch implementation of "Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework"

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Equivariance in PointMLP

smiles724 opened this issue · comments

Hi thanks for your sharing.
However, I am curious about your initialization of point embeddings. You used a Conv1D to initialize the point feature, where the input channel is 3, the coordinates of each point.

I wonder whether this kind of initialization can lead to different results when the coordinate system changes. In other words, how do you ganrantee the equivariance of your network?

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Please see more direct figure in your paper. You directly change (1024, 3) to (1024, 64).
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