- vanillaLSTM : Encoder LSTM decoded by a Dense Layer. Single Shot RNN that predict the output sequence once.
- seq2seq : A classical sequence2sequence RNN. Encoder LSTM and Decoder LSTM, so it keeps Time dependancy in the decoder.
- seq2seqAttention : Similar to
seq2seqwith the add of Luong Attention.
- pointnet : Network used to perform classification, semantic-segmentation and part-segmentation tasks with Points Clouds
- pointnet_foldingnet : Autoencoder for points clouds data. Encoder is based on pointnet and decoder on foldingnet.
- foldingnet : Foldingnet, autoencoder for point clouds : (B,N,3) -> (B,M,3), with M a square number
- ASPP : ASPP for Atrous Spatial Pyramid Pooling
- unet : CNN used for semantic segmentation
- wcce : Weighted Categorical Cross Entropy, used for imbalanced classification datasets. Take a weights list in parameters.
- dice_loss : Dice Loss function, mainly used in semantic segmentation
- chamfer_loss : Distance used to compare a B point clouds of shape [B,N,3] with B point clouds of shape [B,M,3]