NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Results
This challenge addresses the domain-specific problem of enhancing resolution in light field images for computer vision applications, though it is incremental as it builds on existing super-resolution techniques.
The paper summarizes the NTIRE 2023 challenge on light field image super-resolution, which tackled the problem of super-resolving LF images with a 4× magnification under bicubic degradation, resulting in new state-of-the-art methods that achieved up to 1 dB PSNR improvement over prior approaches.
In this report, we summarize the first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4. This challenge develops a new LF dataset called NTIRE-2023 for validation and test, and provides a toolbox called BasicLFSR to facilitate model development. Compared with single image SR, the major challenge of LF image SR lies in how to exploit complementary angular information from plenty of views with varying disparities. In total, 148 participants have registered the challenge, and 11 teams have successfully submitted results with PSNR scores higher than the baseline method LF-InterNet \cite{LF-InterNet}. These newly developed methods have set new state-of-the-art in LF image SR, e.g., the winning method achieves around 1 dB PSNR improvement over the existing state-of-the-art method DistgSSR \cite{DistgLF}. We report the solutions proposed by the participants, and summarize their common trends and useful tricks. We hope this challenge can stimulate future research and inspire new ideas in LF image SR.