ConvPoint: Continuous Convolutions for Point Cloud Processing

Understand

Point clouds are unstructured and unordered data, as opposed to images.

• Thus, most machine learning approach developed for image cannot be directly transferred to point clouds.
• In this paper, we propose a generalization of discrete convolutional neural networks (CNNs) in order to deal with point clouds by replacing discrete kernels by continuous ones.
• This formulation is simple, allows arbitrary point cloud sizes and can easily be used for designing neural networks similarly to 2D CNNs.