Set5

doi:doi:10.57702/ff6krrl0

Set5

The dataset used in the paper is a synthetic dataset for blind super-resolution, consisting of low-resolution images and their corresponding blur kernels.

BibTex:

@dataset{Jian-Nan_Su_and_Min_Gan_and_Guang-Yong_Chen_and_Jia-Li_Yin_and_C_L_Philip_Chen_2024,
    abstract = {The dataset used in the paper is a synthetic dataset for blind super-resolution, consisting of low-resolution images and their corresponding blur kernels.},
    author = {Jian-Nan Su and Min Gan and Guang-Yong Chen and Jia-Li Yin and C. L. Philip Chen},
    doi = {10.57702/ff6krrl0},
    institution = {No Organization},
    keyword = {'32x32', 'Benchmark Dataset', 'Blind Super-Resolution', 'Gaussian Blur', 'HR images', 'High Resolution', 'Image Denoising', 'Image Reconstruction', 'Image Restoration', 'Image Super-Resolution', 'LR images', 'Lightweight Network', 'Low Resolution', 'Low-Complexity', 'Set5', 'Single Image Super-Resolution', 'Testing', 'Training Dataset', 'dataset', 'deep learning', 'image', 'image degradation', 'image restoration', 'image super resolution', 'image super-resolution'},
    month = {dec},
    publisher = {TIB},
    title = {Set5},
    url = {https://service.tib.eu/ldmservice/dataset/set5},
    year = {2024}
}