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.

翻译：本报告总结了首届NTIRE光场（LF）图像超分辨率（SR）挑战赛，该赛事旨在以4倍放大因子的标准双三次退化方式对光场图像进行超分辨率重建。本次挑战赛开发了名为NTIRE-2023的新光场数据集用于验证和测试，并提供名为BasicLFSR的工具箱以促进模型开发。与单图像超分辨率相比，光场图像超分辨率的主要挑战在于如何利用来自大量具有不同视差视角的互补角度信息。共有148名参赛者注册了本次挑战赛，其中11支团队成功提交了结果，其PSNR分数均高于基线方法LF-InterNet \cite{LF-InterNet}。这些新开发的方法在光场图像超分辨率领域树立了新的标杆，例如，优胜方法在现有最先进方法DistgSSR \cite{DistgLF}的基础上实现了约1 dB的PSNR提升。我们报告了参赛者提出的解决方案，并总结了它们的共同趋势和实用技巧。希望本次挑战赛能激发光场图像超分辨率领域的未来研究并催生新思路。