Abstract: Convolution has been the core ingredient of modern neural networks, triggering the surge of deep learning in vision. In this work, we rethink the inherent principles of standard convolution ...
Abstract: Representing valuable semantics in irregular 3-D point clouds with spatial-variant relationships is challenging. Current shared/weighted point convolution methods have limited efficiency and ...
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