The Second Challenge on Real-World Face Restoration at NTIRE 2026: Methods and Results
This challenge benchmarks and advances real-world face restoration methods for the computer vision community.
The NTIRE 2026 challenge on real-world face restoration attracted 96 registrants, with 10 teams submitting valid models and 9 achieving valid scores, advancing state-of-the-art solutions for perceptual quality and identity consistency.
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.