Awesome
Learning Dual-Level Implicit Representation for Real-World Scale Arbitrary Super-Resolution
1. RealArbiSR Dataset Preparation
Version 2
In version 2, we further refine the dataset quality and increase the size of x1.7/x2.3/x2.7/x3.3/x3.7 testset from 83 scenes to 100 scenes.
Dataset Version 2 is available at RealArbiSRdatasetv2 - Google Drive
The pretrained models and the PSNR results of RealArbiSR dataset Version 2 are listed below:
Methods | PSNR | x1.5 | x2.0 | x2.5 | x3.0 | x3.5 | x4.0 |
---|---|---|---|---|---|---|---|
Bicubic | 34.87 | 31.61 | 29.81 | 28.56 | 27.64 | 27.00 | |
EDSR-LIIF | 36.55 | 33.63 | 31.76 | 30.49 | 29.47 | 28.80 | |
EDSR-LTE | 36.56 | 33.63 | 31.75 | 30.48 | 29.52 | 28.84 | |
EDSR-CiaoSR | 36.67 | 33.84 | 32.01 | 30.74 | 29.75 | 29.01 | |
EDSR-DDIR | 36.91 | 34.09 | 32.20 | 30.94 | 29.94 | 29.19 | |
RDN-LIIF | 36.64 | 33.84 | 31.94 | 30.69 | 29.69 | 29.00 | |
RDN-LTE | 36.60 | 33.80 | 31.95 | 30.67 | 29.70 | 29.00 | |
RDN-CiaoSR | 36.85 | 34.07 | 32.18 | 30.87 | 29.86 | 29.10 | |
RDN-DDIR | 37.04 | 34.28 | 32.35 | 31.05 | 30.04 | 29.26 |
Methods | PSNR | x1.7 | x2.3 | x2.7 | x3.3 | x3.7 |
---|---|---|---|---|---|---|
Bicubic | 31.31 | 28.54 | 27.51 | 26.42 | 25.83 | |
EDSR-LIIF | 33.37 | 30.57 | 29.37 | 28.02 | 27.32 | |
EDSR-LTE | 33.47 | 30.64 | 29.40 | 28.02 | 27.30 | |
EDSR-CiaoSR | 33.04 | 30.58 | 29.50 | 28.23 | 27.48 | |
EDSR-DDIR | 33.71 | 30.97 | 29.76 | 28.37 | 27.64 | |
RDN-LIIF | 33.49 | 30.71 | 29.51 | 28.16 | 27.43 | |
RDN-LTE | 33.54 | 30.83 | 29.61 | 28.23 | 27.51 | |
RDN-CiaoSR | 33.16 | 30.81 | 29.74 | 28.44 | 27.69 | |
RDN-DDIR | 33.77 | 31.06 | 29.85 | 28.46 | 27.72 |
Version 1 (used in the original paper)
Dataset is available at RealArbiSRdataset - Google Drive.
Arrange dataset into the path like load/Train/...
and load/Test/...
2. DDIR Code
Train
python train_realliif_deform.py --gpu [GPU] --config [CONFIG_NAME] --save_name [SAVE_NAME]
Test on Pretrained Models
The pretrained models (for Verision 1, used in the original paper) can be downloaded from the google drive links below:
To test at all scale factors:
bash ./scripts/test-realsrarbi-deform.sh [MODEL_PATH] [GPU]
Citation
If you find this code useful in your work then please cite:
@article{li2024learning,
title={Learning Dual-Level Deformable Implicit Representation for Real-World Scale Arbitrary Super-Resolution},
author={Li, Zhiheng and Li, Muheng and Fan, Jixuan and Chen, Lei and Tang, Yansong and Zhou, Jie and Lu, Jiwen},
journal={arXiv preprint arXiv:2403.10925},
year={2024}
}
Contact
Please contact Zhiheng Li @ lizhihan21@mails.tsinghua.edu.cn if any issue.
Acknowledgements
This code is built on LIIF. We thank the authors for sharing their codes.