3Doodle

Official implementation of 3Doodle: Compact Abstraction of Objects with 3D Strokes, SIGGRAPH (ACM Transactions on Graphics) 2024.

Project Page | Paper | arXiv

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Installation

Create a conda environment and install required libraries.

conda env create -f environment.yml
# set your own CUDA path in the activate.sh file
source activate.sh

Install other dependencies and this package.

# Install CLIP
pip install git+https://github.com/openai/CLIP.git

# Install Open3D
pip install open3d

# Install robust loss
pip install git+https://github.com/jonbarron/robust_loss_pytorch

# Install diffvg
git clone https://github.com/BachiLi/diffvg
cd diffvg
git submodule update --init --recursive
python setup.py install
cd ..

# Install pytorch3d
pip install fvcore
# Replace the version str (py39...pyt1121) with your corresponding python and torch version
pip install --no-index --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py39_cu113_pyt1121/download.html

# Remaining dependencies
pip install -r requirements.txt

# Install this package
pip install -e .

Dawn wrote a detailed instruction to setup environment in issue #9, so if you encounter any problem during installation, please refer to it.

Dataset

You can download our dataset and SfM point clouds from this link.

Train

# Bézier curve only
python train.py --config configs/nerf_synthetic/mic.yaml -ep sanity_check -eg bezier -en mic
# with superquadrics
python train.py --config configs/3doodle_sq/snowman.yaml --stages all -ep sanity_check -eg all -en snowman

Render test images

# Bézier curve only
python test_render.py --config logs/sanity_check/bezier/mic_0/config.yaml -ck logs/sanity_check/bezier/mic_0/best.ckpt
# with superquadrics
python test_render.py --config logs/sanity_check/all/snowman_0/config.yaml --stages all -ck logs/sanity_check/all/snowman_0/best.ckpt

Real-time interactive viewer

# Bézier curve only
python viewer.py --config logs/sanity_check/bezier/mic_0/config.yaml -ck logs/sanity_check/bezier/mic_0/best.ckpt
# with superquadrics
python viewer.py --config logs/sanity_check/all/snowman_0/config.yaml --stages all -ck logs/sanity_check/all/snowman_0/best.ckpt

3Doodle_viewer.mp4

Acknowledgements

We thank our friend Clément Jambon for helping with the implementation of the interactive viewer. We would like to clarify that the source codes related to the interactive viewer are borrowed from his work.

Citation

Please cite as below if you find this paper and repository are helpful to you:

@article{10.1145/3658156,
    author = {Choi, Changwoon and Lee, Jaeah and Park, Jaesik and Kim, Young Min},
    title = {3Doodle: Compact Abstraction of Objects with 3D Strokes},
    year = {2024},
    issue_date = {July 2024},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    volume = {43},
    number = {4},
    issn = {0730-0301},
    url = {https://doi.org/10.1145/3658156},
    doi = {10.1145/3658156},
    journal = {ACM Trans. Graph.},
    month = {jul},
    articleno = {107},
    numpages = {13},
    keywords = {3D sketch lines, 3D strokes, differentiable rendering}
}