The Second Challenge on Real-World Face Restoration at NTIRE 2026: Methods and Results

Journal: arXiv
Published Date:

Abstract

This paper provides a review of the NTIRE 2026 challenge on real-world face restoration, highlighting the proposed solutions and the resulting outcomes. The challenge focuses on generating natural and realistic outputs while maintaining identity consistency. Its goal is to advance state-of-the-art solutions for perceptual quality and realism, without imposing constraints on computational resources or training data. Performance is evaluated using a weighted image quality assessment (IQA) score and employs the AdaFace model as an identity checker. The competition attracted 96 registrants, with 10 teams submitting valid models; ultimately, 9 teams achieved valid scores in the final ranking. This collaborative effort advances the performance of real-world face restoration while offering an in-depth overview of the latest trends in the field.

Authors

  • Jingkai Wang; Jue Gong; Zheng Chen; Kai Liu; Jiatong Li; Yulun Zhang; Radu Timofte; Jiachen Tu; Yaokun Shi; Guoyi Xu; Yaoxin Jiang; Jiajia Liu; Yingsi Chen; Yijiao Liu; Hui Li; Yu Wang; Congchao Zhu; Alexandru-Gabriel Lefterache; Anamaria Radoi; Chuanyue Yan; Tao Lu; Yanduo Zhang; Kanghui Zhao; Jiaming Wang; Yuqi Li; WenBo Xiong; Yifei Chen; Xian Hu; Wei Deng; Daiguo Zhou; Sujith Roy; Claudia Jesuraj; Vikas B; Spoorthi LC; Nikhil Akalwadi; Ramesh Ashok Tabib; Uma Mudenagudi; Yuxuan Jiang; Chengxi Zeng; Tianhao Peng; Fan Zhang; David Bull Wei Zhou; Linfeng Li; Hongyu Huang; Hoyoung Lee; SangYun Oh; ChangYoung Jeong; Axi Niu; Jinyang Zhang; Zhenguo Wu; Senyan Qing; Jinqiu Sun; Yanning Zhang