Video Matting via Consistency-Regularized Graph Neural Networks
Project Page | Real Data | Paper
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
- Please see the real data in the above link.
- Please contact Tiantian Wang ([email protected]) 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.