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code for paper Differentiable Surface Splatting for Point-based Geometry Processing
- clone
git clone --recursive https://gitlab.inf.ethz.ch/OU-SORKINE/dss.git
cd dss- install prequisitories. Our code uses python3.7, the installation instruction requires the latest anaconda.
# install cuda, cudnn, nccl from nvidia
# we tested with cuda 10.1, cudnn 7.5, nccl 1.3.5
# update conda
conda update -n base -c defaults conda
# install requirements
conda config --add channels pytorch
conda config --add channels conda-forge
conda create --name DSS --file requirements.txt
conda activate DSS
# plyfile package is not on conda
pip install plyfile- compile cuda library
cd pytorch_points
python setup.py install
cd ..
python setup.py developpython learn_shape_from_target.py -t example_data/scenes/good_teapot.json
# inverse rendering test: optimize point positions and normals to transform sphere to teapot
python learn_shape_from_target.py example_data/scenes/sphere.json -t example_data/scenes/teapot.json
python learn_shape_from_target.py example_data/scenes/cube_20k.json -t example_data/scenes/yoga6.json --name yoga6_z_paper_1
python finetune_shape.py learn_examples/yoga6_z_paper_1/final_scene.json -t example_data/scenes/yoga6.json --name yoga6_z_paper_1_1
cd trained_models
# unix system can run this command directly
./download_data.sh# 0.3% noise
python learn_image_filter.py example_data/scenes/pix2pix_denoise.json --cloud example_data/pointclouds/noisy03_points/a72-seated_jew_aligned_pca.ply
# 1.0% noise
python learn_image_filter.py example_data/scenes/pix2pix_denoise_noise01.json --cloud example_data/noisy1_points/a72-seated_jew_aligned_pca.ply
python sequences.py example_data/scenes/teapot.json --points example_data/pointclouds/teapot_normal_dense.ply --width 512 --height 512 --output renders/teapot_360
# then you can create gif. on ubuntu this can be done with
convert -dispose 2 -delay 10 renders/teapot_360/*.png renders/teapot_360/animation.gif
Please cite us if you find the code useful!
@article{Yifan:DSS:2019,
author = {Yifan, Wang and
Serena, Felice and
Wu, Shihao and
{\"{O}}ztireli, Cengiz and
Sorkine{-}Hornung, Olga},
title = {Differentiable Surface Splatting for Point-based Geometry Processing},
journal = {ACM Transactions on Graphics (proceedings of ACM SIGGRAPH ASIA)},
volume = {38},
number = {6},
year = {2019},
}
We would like to thank Federico Danieli for the insightful discussion, Phillipp Herholz for the timely feedack, Romann Weber for the video voice-over and Derek Liu for the help during the rebuttal. This work was supported in part by gifts from Adobe, Facebook and Snap, Inc.