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.vscode
 
 
deep_sdf
deep_sdf
 
 
examples
examples
 
 
icp
icp
 
 
networks
networks
 
 
old
old
 
 
pcl_normal
pcl_normal
 
 
src
src
 
 
trained_model
trained_model
 
 
CMakeLists.txt
CMakeLists.txt
 
 
CODE_OF_CONDUCT.md
CODE_OF_CONDUCT.md
 
 
CONTRIBUTING.md
CONTRIBUTING.md
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 
Training loss for chairs.png
Training loss for chairs.png
 
 
Transformation_loss_new.png
Transformation_loss_new.png
 
 
bias_new.pt
bias_new.pt
 
 
bias_withoutdiag.pt
bias_withoutdiag.pt
 
 
evaluate.py
evaluate.py
 
 
evaluate_deepsdf_new.py
evaluate_deepsdf_new.py
 
 
evaluate_deepsdf_vtk.py
evaluate_deepsdf_vtk.py
 
 
heatmap.png
heatmap.png
 
 
heatmap_new.png
heatmap_new.png
 
 
pcl_normal.cpp
pcl_normal.cpp
 
 
plot_log.py
plot_log.py
 
 
preprocess_data.py
preprocess_data.py
 
 
reconstruct.py
reconstruct.py
 
 
test_model.pts
test_model.pts
 
 
test_model_pcd.pcd
test_model_pcd.pcd
 
 
train_deep_sdf.py
train_deep_sdf.py
 
 
train_deep_sdf_vtk.py
train_deep_sdf_vtk.py
 
 
transform_matrix_new.pt
transform_matrix_new.pt
 
 
transform_matrix_withoutdiag.pt
transform_matrix_withoutdiag.pt
 
 
transform_points_new.pts
transform_points_new.pts
 
 

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DeepSDF

This is an implementation of point cloud registration using the CVPR '19 paper "DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation" by Park et al. See the paper [here][6].

Code adopted from original DeepSDF repo

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