One-Trimap Video Matting (ECCV 2022)
_{Hongje Seong, Seoung Wug Oh, Brian Price, Euntai Kim, Joon-Young Lee}

[Paper] [Demo video]

Official Pytorch implementation of the ECCV 2022 paper, "One-Trimap Video Matting".

Environments

• Ubuntu 18.04
• python 3.8
• pytorch 1.8.2
• CUDA 10.2

Environment setting

conda create -n otvm python=3.8
conda activate otvm
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch-lts
pip install opencv-contrib-python scikit-image scipy tqdm imgaug yacs albumentations

Dataset

To train OTVM, you need to prepare AIM and VideoMatting108 datasets

PATH/TO/DATASET
├── Combined_Dataset
│   ├── Adobe Deep Image Mattng Dataset License Agreement.pdf
│   ├── README.txt
│   ├── Test_set
│   │   ├── Adobe-licensed images
│   │   └── ...
│   └── Training_set
│       ├── Adobe-licensed images
│       └── ...
└── VideoMatting108
    ├── BG_done2
    │   ├── airport
    │   └── ...
    ├── FG_done
    │   ├── animal_still
    │   └── ...
    ├── flow_png_val
    │   ├── animal_still
    │   └── ...
    ├── frame_corr.json
    ├── train_videos_subset.txt
    ├── train_videos.txt
    ├── val_videos_subset.txt
    └── val_videos.txt

Training

Download pre-trained weights

Download the pre-trained weights from here and put them in the weight/ directory.

mkdir weights
mv STM_weights.pth weights/
mv FBA.pth weights/
mv s1_OTVM_trimap.pth weights/
mv s1_OTVM_alpha.pth weights/
mv s2_OTVM_alpha.pth weights/
mv s3_OTVM.pth weights/
mv s4_OTVM.pth weights/

Note: Initial weights of the trimap propagation and alpha prediction networks were taken from STM and FBA, respectively.

Change DATASET.PATH in config.py

vim config.py

# Change below path
_C.DATASET.PATH = 'PATH/TO/DATASET'

Stage-wise Training

# options: scripts/train_XXX.sh [GPUs]
bash scripts/train_s1_trimap.sh 0,1,2,3
bash scripts/train_s1_alpha.sh 0,1,2,3
bash scripts/train_s2_alpha.sh 0,1,2,3
bash scripts/train_s3.sh 0,1,2,3
bash scripts/train_s4.sh 0,1,2,3

Inference (VideoMatting108 dataset)

# options: scripts/eval_s4.sh [GPU]
bash scripts/eval_s4.sh 0

Inference (custom dataset)

# options: scripts/eval_s4_demo.sh [GPU]
# The results will be generated in: ./demo_results
bash scripts/eval_s4_demo.sh 0

Bibtex

@inproceedings{seong2022one,
  title={One-Trimap Video Matting},
  author={Seong, Hongje and Oh, Seoung Wug and Price, Brian and Kim, Euntai and Lee, Joon-Young},
  booktitle={European Conference on Computer Vision},
  year={2022}
}

Terms of Use

This software is for non-commercial use only. The source code is released under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) Licence (see this for details)

Acknowledgments

This code is based on TCVOM (ACM MM 2021): [link]