# PointCNN: Convolution On $\mathcal{X}$-Transformed Points

Yangyan LiRui BuMingchao SunWei WuXinhan DiBaoquan Chen

We present a simple and general framework for feature learning from point clouds. The key to the success of CNNs is the convolution operator that is capable of leveraging spatially-local correlation in data represented densely in grids (e.g. images)... (read more)

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