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VideoMatting-CRGNN

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# Video Matting via Consistency-Regularized Graph Neural Networks
### [Project Page]() | [Real Data](https://www.dropbox.com/sh/23uvsue5we7e7b5/AAB4GSSWIaKiSouvN3wuWiwWa?dl=0) | [Paper](https://faculty.ucmerced.edu/mhyang/papers/iccv2021_video_matting.pdf)

## Installation
Our code has been tested on Python 3.7, cuda 10.1 and PyTorch 1.4.0.

pip install -r requirements.txt
	# install dcn
	cd models/archs/dcn
	python setup.py develop

## Inference
Run the following command to do inference of CRGNN on the video matting dataset:

python test.py

## Data
1. Please see the real data in the above link.
2. Please contact Tiantian Wang (tiantianwang.ice@gmail.com) if you need composited data.

## Citation
If you find this work or code useful for your research, please cite:
```
@inproceedings{wang2021crgnn,
  title={Video Matting via Consistency-Regularized Graph Neural Networks},
  author={Wang, Tiantian and Liu, Sifei and Tian, Yapeng and Li, Kai and Yang, Ming-Hsuan},
  booktitle={Proc. IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2021}
}

```

## Permission and Disclaimer
This code is only for non-commercial purposes. As covered by the ADOBE IMAGE DATASET LICENSE AGREEMENT, the trained models included in this repository can only be used/distributed for non-commercial purposes. Anyone who violates this rule will be at his/her own risk.

VideoMatting-CRGNN

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