YinQian18 / D3Dnet

Repository for "Deformable 3D Convolution for Video Super-Resolution", arXiv, 2020

Deformable 3D Convolution for Video Super-Resolution

Pytorch implementation of deformable 3D convolution network (D3Dnet). [PDF]

Our code is based on cuda and can perform deformation in any dimension of 3D convolution.

Code will be released soon.

Architecture of D3Dnet

Architecture of D3D

Quantitative Results

Table 1. PSNR/SSIM achieved by different methods.

Table 2. T-MOVIE and MOVIE achieved by different methods.

We have organized the Matlab code framework of Video Quality Assessment metric T-MOVIE and MOVIE. [Code]
Welcome to have a look and use our code.

Qualitative Results

Qualitative results achieved by different methods. Blue boxes represent the temporal profiles among different frames.

Citiation

@article{D3Dnet,
  author = {Ying, Xinyi and Wang, Longguang and Wang, Yingqian and Sheng, Weidong and An, Wei and Guo, Yulan},
  title = {Deformable 3D Convolution for Video Super-Resolution},
  journal = {arXiv preprint arXiv:2004.02803},
  year = {2020},
}

Contact

Please contact us at [e-mail] for any question.