Efficient Light Field Image Super-Resolution via Progressive Disentangling

This repository contains official pytorch implementation of Efficient Light Field Image Super-Resolution via Progressive Disentangling, accepted by NTIRE 2024, done by Gaosheng Liu, Huanjing Yue, and Jingyu Yang.

Dataset

We use the processed data by LF-DFnet, including EPFL, HCInew, HCIold, INRIA and STFgantry datasets for training and testing. Please download the dataset in the official repository of LF-DFnet.

Code

Dependencies

• Ubuntu 18.04
• Python 3.6
• Pyorch 1.3.1 + torchvision 0.4.2 + cuda 92
• Matlab

Prepare Test Data

• Please refer to the previous work for data generation

Test

• Run:

  python test.py

Citation

If you find this work helpful, please consider citing the following papers:

@inproceedings{liu2024efficient,
  title={Efficient Light Field Image Super-Resolution via Progressive Disentangling},
  author={Liu, Gaosheng and Yue, Huanjing and Yang, Jingyu},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={6277--6286},
  year={2024}
}