NTIRE 2023 Challenge on Image Super-Resolution (×4): Methods and Results
Yulun Zhang, Kai Zhang, Zheng Chen, Yawei Li, Radu Timofte, Junpei Zhang, Kexin Zhang, Rui Hui Peng, Yanbiao Ma, Licheng Jia, Huaibo Huang, Xiaoqiang Zhou, Yuang Ai, Ran He, Yajun Qiu, Qiang Zhu, Pengfei Li, Qianhui Li, Shuyuan Zhu, Dafeng Zhang · 2023
This paper reviews the NTIRE 2023 challenge on image super-resolution (×4), focusing on the proposed solutions and results. The task of image super-resolution (SR) is to generate a high-resolution (HR) output from a corresponding low-resolution (LR) input by leveraging prior information from paired LR-HR images. The aim of the challenge is to obtain a network design/solution capable to produce high-quality results with the best performance (e.g., PSNR). We want to explore how high performance we can achieve regardless of computational cost (e.g., model size and FLOPs) and data. The track of the challenge was to measure the restored HR images with the ground truth HR images on DIV2K testing dataset. The ranking of the teams is determined directly by the PSNR value. The challenge has attracted 192 registered participants, where 15 teams made valid submissions. They achieve state-of-the-art performance in single image super-resolution.