This is an official repository of paper "Combinatorial 3D Shape Generation via Sequential Assembly".
- arXiv Preprint: (abs), (pdf)
- High-Resolution Version (About 50MB)
You are able to install required Python packages by commanding pip install -r requirements.txt
.
- Creating a dataset
Run the following script.
# Move to src_dataset/
$ ./dataset_all.sh
It will create a dataset, which has already been included in the repository.
- Generating a 3D shape
# Move to src_generation/
$ python assemble_with_bo.py --ind_class 21 --ind_target 1 --use_stability --use_rollback
ind_class
and ind_target
indicate the indices of class and target object, respectively (Please check the code for dataset creation).
use_stability
and use_rollback
are flags for considering stability and using a rollback step.
- Creating an XML file and its corresponding PLY files
Run the following script.
# Move to src_rendering/
$ ./meshes_all.sh
It requires a rendering process with Mitsuba renderer. After changing the camera position and its perspective, render the XML file you want.
- Bar
- Line
- Plate
- Wall
- Cuboid
- Square Pyramid
- Chair
- Sofa
- Cup
- Hollow
- Table
- Car
@article{KimJ2020arxiv,
author={Kim, Jungtaek and Chung, Hyunsoo and Lee, Jinhwi and Cho, Minsu and Park, Jaesik},
title={Combinatorial {3D} Shape Generation via Sequential Assembly},
journal={{arXiv} preprint {arXiv}:2004.07414},
year={2020}
}
or
@inproceedings{KimJ2020neuripsw,
author={Kim, Jungtaek and Chung, Hyunsoo and Lee, Jinhwi and Cho, Minsu and Park, Jaesik},
title={Combinatorial {3D} Shape Generation via Sequential Assembly},
booktitle={NeurIPS Workshop on Machine Learning for Engineering Modeling, Simulation, and Design (ML4Eng)},
year={2020}
}
- Jungtaek Kim: jtkim@postech.ac.kr
- Hyunsoo Chung: hschung2@postech.ac.kr