NTIRE 2025 Challenge on Light Field Image Super-Resolution: Methods and Results

Yingqian Wang, Zhengyu Liang, Fengyuan Zhang, Lvli Tian, Longguang Wang, Juncheng Li, Jungang Yang, Radu Timofte, Yulan Guo, Kai Jin, Zeqiang Wei, Angulia Yang, Di Wu, Mingzhi Gao, Xiuzhuang Zhou, Yue Yan, Yuaho Wang, Shuang Chen, Zeping Tian, Yizhi Hu et al. (54 additional authors not shown)

Abstract: This report summarizes the 3rd NTIRE challenge on light field (LF) image super-resolution (SR), focusing on novel methods and their outcomes. This challenge aims to super-resolve LF images degraded by bicubic downsampling, and comprises three tracks: a classical track, an efficiency track, and a large model track. In total, 308 participants registered, and 13 teams submitted results that outperformed the baseline methods. The challenge has established a new state-of-the-art in LF image SR, e.g., the winning method in Track 1 achieves a 0.36 dB PSNR improvement over last year's champion on the test set. We present the submitted solutions, analyze their common trends, and highlight practical techniques. We hope this challenge will inspire further advancements in LF image SR.

External IDs:dblp:conf/cvpr/WangLZTW00TGJWY25