Monte Carlo convolution for learning on non-uniformly sampled point clouds
Monte Carlo convolution for learning on non-uniformly sampled point clouds
Deep learning systems extensively use convolution operations to process input data. Though convolution is clearly defined for structured data such as 2D images or 3D volumes, this is not true for other data types such as sparse point clouds. Previous techniques have developed approximations to convolutions for restricted conditions. Unfortunately, …