MODNet: Is a Green Screen Really Necessary for Real-Time Portrait Matting?
Arxiv Preprint |
Supplementary Video |
Video Matting Demo :fire: |
Image Matting Demo :fire:
This is the official project of our paper Is a Green Screen Really Necessary for Real-Time Portrait Matting?
MODNet is a trimap-free model for portrait matting in real time (on a single GPU).
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## News
- [Dec 10 2020] Release [Video Matting Demo](https://colab.research.google.com/drive/1Pt3KDSc2q7WxFvekCnCLD8P0gBEbxm6J?usp=sharing) and [Image Matting Demo](https://colab.research.google.com/drive/1GANpbKT06aEFiW-Ssx0DQnnEADcXwQG6?usp=sharing).
- [Nov 24 2020] Release [Arxiv Preprint](https://arxiv.org/pdf/2011.11961.pdf) and [Supplementary Video](https://youtu.be/PqJ3BRHX3Lc).
## Video Matting Demo
We provide two real-time portrait video matting demos based on WebCam.
If you have an Ubuntu system, we recommend you to try the [offline demo](demo/video_matting/README.md) to get a higher *fps*. Otherwise, you can access the [online Colab demo](https://colab.research.google.com/drive/1Pt3KDSc2q7WxFvekCnCLD8P0gBEbxm6J?usp=sharing).
## Image Matting Demo
We provide an [online Colab demo](https://colab.research.google.com/drive/1GANpbKT06aEFiW-Ssx0DQnnEADcXwQG6?usp=sharing) for portrait image matting.
It allows you to upload portrait images and predict/visualize/download the alpha mattes.
## TO DO
- Release training code (scheduled in **Jan. 2021**)
- Release PPM-100 validation benchmark (scheduled in **Feb. 2021**)
## Acknowledgement
We thank [City University of Hong Kong](https://www.cityu.edu.hk/) and [SenseTime](https://www.sensetime.com/) for their support to this project.
## Citation
If this work helps your research, please consider to cite:
```bibtex
@article{MODNet,
author = {Zhanghan Ke and Kaican Li and Yurou Zhou and Qiuhua Wu and Xiangyu Mao and Qiong Yan and Rynson W.H. Lau},
title = {Is a Green Screen Really Necessary for Real-Time Portrait Matting?},
journal={ArXiv},
volume={abs/2011.11961},
year = {2020},
}
```
## Contact
This project is currently maintained by Zhanghan Ke ([@ZHKKKe](https://github.com/ZHKKKe)).
If you have any questions, please feel free to contact `kezhanghan@outlook.com`.