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MFQEv2 Dataset
For some video enhancement/restoration tasks, lossless reference videos are necessary.
We open-source the dataset used in our MFQEv2 paper, which includes 108 lossless YUV videos for training and 18 test videos recommended by ITU-T.
1. Content
- 108 lossless YUV videos for training.
- 18 lossless YUV videos for test, recommended by ITU-T.
- An HEVC compression tool box.
43.1 GB in total.
2. Download Raw Videos
3. Compress Videos
We compress both training and test videos by HM 16.5 at low delay P (LDP) mode with QP=37. The video compression toolbox is provided at the dataset folder.
We will get:
MFQEv2_dataset/
├── train_108/
│ ├── raw/
│ └── HM16.5_LDP/
│ └── QP37/
├── test_18/
│ ├── raw/
│ └── HM16.5_LDP/
│ └── QP37/
├── video_compression/
│ └── ...
└── README.md
Ubuntu
cd video_compression/
- Edit
option.yml
. chmod +x TAppEncoderStatic
python unzip_n_compress.py
Windows
- Unzip
train_108.zip
andtest_18.zip
manually! cd video_compression\
- Edit
option.yml
(e.g.,system: windows
). python unzip_n_compress.py
4. Citation
If you find this helpful, please star and cite:
@article{2019xing,
doi = {10.1109/tpami.2019.2944806},
url = {https://doi.org/10.1109%2Ftpami.2019.2944806},
year = 2021,
month = {mar},
publisher = {Institute of Electrical and Electronics Engineers ({IEEE})},
volume = {43},
number = {3},
pages = {949--963},
author = {Zhenyu Guan and Qunliang Xing and Mai Xu and Ren Yang and Tie Liu and Zulin Wang},
title = {{MFQE} 2.0: A New Approach for Multi-Frame Quality Enhancement on Compressed Video},
journal = {{IEEE} Transactions on Pattern Analysis and Machine Intelligence}
}
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