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arXiv:2604.10532 (cs)
[Submitted on 12 Apr 2026 (v1), last revised 15 Apr 2026 (this version, v2)]

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

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 V, 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
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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.
Comments: NTIRE 26: this https URL . NTIRE Real-World Face Restoration: this https URL . CVPR 2026 Workshop
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2604.10532 [cs.CV]
  (or arXiv:2604.10532v2 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2604.10532

Submission history

From: Jingkai Wang [view email]
[v1] Sun, 12 Apr 2026 08:49:14 UTC (7,015 KB)
[v2] Wed, 15 Apr 2026 11:48:29 UTC (7,015 KB)
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