Repository for Detail-revealing Deep Video Super-resolution https://arxiv.org/abs/1704.02738
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README.md

Detail-revealing Deep Video Super-resolution

by Xin Tao, Hongyun Gao, Renjie Liao, Jue Wang, Jiaya Jia. (pdf)

Our results on real data:

Real

Our results compared with other state-of-the-arts:

Comparisons

SPMCS Dataset

We have release the testing set of SPMCS. download

It consists 30 different videos, each of them contains 31 frames.

Each sequence contains bicubic downsampled input for x2, x3, x4 scale factors. Folder truth contains high-resolution ground truth image for calculating PSNR and SSIM.

Since many previous methods use 31 frames to produce one result for central frame, we also evaluate quantative result only for the central frame (the number in our paper). We do not crop boundary or use other postprocessing.

We evaluete PSNR and SSIM only for Y channel of YUV color space.

Code v0.1

Currently, we release our research code for testing. It should produce the same results as in the paper for scale factor x2 & x4 and frame number 3.

Testing

It would be very easy to understand the test() function and test on your own data.

Training

We will update the code for training and better reading after recent paper deadline.

Video Results

Here we provide video results for 15 sequences for visual and quantitative comparisons. videos pngs

Citation

If you use any part of our code, or SPMC video SR is useful for your research, please consider citing:

@InProceedings{tao2017spmc,
  author    = {Xin Tao and
               Hongyun Gao and
               Renjie Liao and
               Jue Wang and
               Jiaya Jia},
  title = {Detail-Revealing Deep Video Super-Resolution},
  booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
  month = {Oct},
  year = {2017}
}

Contact

We are glad to hear if you have any suggestions, questions about implementation or sequences for testing.

Please send email to xtao@cse.cuhk.edu.hk