Super-resolution (SR) is the technique of increasing the nominal resolution
of image / video content accompanied with quality improvement. Video
super-resolution (VSR) can be considered as the generalization of single image
super-resolution (SISR). This generalization should be such that more detail is
created in the output using adjacent input frames. In this paper, we propose a
grouped residual in residual network (GRRN) for VSR. By adjusting the
hyperparameters of the proposed structure, we train three networks with
different numbers of parameters and compare their quantitative and qualitative
results with the existing methods. Although based on some quantitative
criteria, GRRN does not provide better results than the existing methods, in
terms of the quality of the output image it has acceptable performance.

超分辨率技术能够提高图像 / 视频内容的名义分辨率，并提高质量。本文提出了一种用于视频超分辨率的分组残差网络（GRRN），通过调整其超参数，训练了三个具有不同参数数量的网络，并将其定量和定性结果与现有方法进行了比较，尽管 GRRN 在一些定量标准上不及现有方法，但在输出图像的质量方面表现仍然可接受。

在残差网络中使用分组残差的视频超分辨率

Video Super-Resolution Using a Grouped Residual in Residual Network

This paper introduces the methods and the results of AIM 2022 challenge on
Instagram Filter Removal. Social media filters transform the images by
consecutive non-linear operations, and the feature maps of the original content
may be interpolated into a different domain. This reduces the overall
performance of the recent deep learning strategies. The main goal of this
challenge is to produce realistic and visually plausible images where the
impact of the filters applied is mitigated while preserving the content. The
proposed solutions are ranked in terms of the PSNR value with respect to the
original images. There are two prior studies on this task as the baseline, and
a total of 9 teams have competed in the final phase of the challenge. The
comparison of qualitative results of the proposed solutions and the benchmark
for the challenge are presented in this report.

本文介绍了 AIM 2022 挑战赛关于 Instagram 滤镜去除的方法和结果，对应用深度学习策略、去除滤镜产生负面影响的问题进行了研究和解决，基于 PSNR 指标对 9 个团队提出的方案进行了比较分析，得出定性结果。