This is the source code([Paper] [Demo] [Training]) repository for three papers:
We released the training codes, a gradio demo (also hosted in huggingface) and the training dataset.
The training dataset can created by code provided in the SSN old repo.
We provide a precomputed dataset composed of 558 different 3D models, which can be downloaded from our huggingface dataset repo. See the ssn_dataset.hdf5 file.
A gradio-based GUI demo is provided in the Demo/SSN folder. First, download the weight it used.
Then run the following code to see the demo:
python app.pyThe training codes are under Train folder. To reproduce the training process, first prepare the dataset discussed above, then run the following command:
cd Train
# before running, try to check the setting in SSN.yaml.
python app/Trainer.py --config configs/SSN.yaml- [2023-03-16] Basic setup.
- SSN dataset/demo/inference/training
- Python environment setup + a docker image
- SSG/PixhtLab dataset/demo/inference/training
This code repo can only be used for non-commercial use only.
If you think the code/dataset is useful, please remember to cite the three papers:
@inproceedings{sheng2023pixht,
title={PixHt-Lab: Pixel Height Based Light Effect Generation for Image Compositing},
author={Sheng, Yichen and Zhang, Jianming and Philip, Julien and Hold-Geoffroy, Yannick and Sun, Xin and Zhang, He and Ling, Lu and Benes, Bedrich},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={16643--16653},
year={2023}
}
@inproceedings{sheng2022controllable,
title={Controllable shadow generation using pixel height maps},
author={Sheng, Yichen and Liu, Yifan and Zhang, Jianming and Yin, Wei and Oztireli, A Cengiz and Zhang, He and Lin, Zhe and Shechtman, Eli and Benes, Bedrich},
booktitle={European Conference on Computer Vision},
pages={240--256},
year={2022},
organization={Springer}
}
@inproceedings{sheng2021ssn,
title={SSN: Soft shadow network for image compositing},
author={Sheng, Yichen and Zhang, Jianming and Benes, Bedrich},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={4380--4390},
year={2021}
}