NTIRE 2026挑战赛推动真实世界人脸修复技术进步
The Second Challenge on Real-World Face Restoration at NTIRE 2026: Methods and Results
- 聚焦自然逼真输出与身份一致性，不限制算力与数据
- 9支队伍在最终排名中获得有效评分，最高得分提升显著
- 采用AdaFace检测身份一致性，提供最新技术趋势分析
本文回顾了NTIRE 2026真实世界人脸修复挑战赛的方案与成果。挑战赛旨在生成自然且真实的修复结果，同时保持身份一致性，不设计算资源或训练数据限制。性能通过加权图像质量评估（IQA）分数衡量，并使用AdaFace模型进行身份一致性检查。共有96人注册，10支队伍提交有效模型，最终9支队伍获得有效排名分数。该赛事推动了真实世界人脸修复的技术进展，并深入呈现了领域最新趋势。
原文摘要 · Abstract (English)
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.
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