NTIRE 2022 Challenge on Learning the Super-Resolution Space

Andreas Lugmayr, Martin Danelljan, Radu Timofte, Kang-Wook Kim, Younggeun Kim, Jae-Young Lee, Zechao Li, Jinshan Pan, Dongseok Shim, Ki-Ung Song, Jinhui Tang, Cong Wang, Zhihao Zhao

Abstract: This paper reviews the NTIRE 2022 challenge on learning the super-Resolution space. This challenge aims to raise awareness that the super-resolution problem is ill-posed. Since many high-resolution images map to the same low-resolution image, we asked the participants to create methods that sample diverse super-resolution from the space of possible high-resolution images given a low-resolution image. For evaluation, we use the same protocol as introduced in the last year’s super-resolution space challenge of NTIRE 2021. We compare the submissions of the participating teams and relate them to the approaches from last year. This challenge contains two tracks: 4× and 8× scale factor. In total, 3 teams competed in the final testing phase.