Rotation Invariant Convolutions for 3D Point Clouds Deep Learning

17 Aug 2019Zhiyuan ZhangBinh-Son HuaDavid W. RosenSai-Kit Yeung

Recent progresses in 3D deep learning has shown that it is possible to design special convolution operators to consume point cloud data. However, a typical drawback is that rotation invariance is often not guaranteed, resulting in networks being trained with data augmented with rotations... (read more)

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