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Implementation of the PointNet networks.
@inproceedings{qi2017pointnet, title={Pointnet: Deep learning on point sets for3d classification and segmentation}, author={Qi, Charles R and Su, Hao and Mo, Kaichun and Guibas, Leonidas J}, booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition}, pages={652--660}, year={2017} }
This shorthand notation is used throughout this module:
B: Number of elements in a batch.
N: The number of points in the point set.
D: Number of dimensions (e.g. 2 for 2D, 3 for 3D).
C: The number of feature channels.
Classes
class ClassificationHead: The PointNet classification head.
class PointNetConv2Layer: The 2D convolution layer used by the feature encoder in PointNet.
class PointNetDenseLayer: The fully connected layer used by the classification head in pointnet.
class PointNetVanillaClassifier: The PointNet 'Vanilla' classifier (i.e. without spatial transformer).
class VanillaEncoder: The Vanilla PointNet feature encoder.