3D Deep Learning Models
Dynamic-Graph CNN
Flux3D.DGCNN — TypeDGCNN(num_classes::Int=10, K::Int=10, npoints::Int=1024)Flux implementation of Dynamic-Graph CNN classification model.
Fields:
num_classes- Number of classes in dataset.K- k nearest neighbour to be used EdgeConv.npoints- Number of points in input PointCloud.
PointNet
Flux3D.PointNet — TypePointNet(num_classes::Int=10, hidden_dims::Int=64)Flux implementation of PointNet classification model.
Fields:
num_classes- Number of classes in dataset.hidden_dims- Hiddem dimension in PointNet model.