Project Report: Project_Report.pdf
Presentation Video: presentation.mp4
To run:
cd pclouds
python download_pclouds.py
cd ..
python train_normalnet.py --indir ./pclouds --nepoch 100 --weight_decay 0.01
To try different symmetric functions, use --sym_op sum or --sym_op max.
To use global features only as the NormalNet input, use --global_feature True. By default, both local and global features are used.
The pretrained model is models/Normal_estimation_model_99.pth.
The train and test losses for our experiments are in losses_log folder. loss_plots.ipynb shows the loss plots.
- This repo is based on this Pytorch implementation of PointNet, https://github.com/fxia22/pointnet.pytorch.