NTIRE 2025挑战赛推动真实场景人脸修复，提升画质与身份一致性。
NTIRE 2025 Challenge on Real-World Face Restoration: Methods and Results
- 采用加权图像质量评估与AdaFace模型综合评测修复效果。
- 13支队伍提交有效模型，10支进入最终排名，共141人注册参赛。
- 不设算力与数据限制，聚焦自然真实感与身份一致性的提升。
本文回顾了NTIRE 2025年真实世界人脸修复挑战赛，重点介绍参赛方案与最终成果。挑战赛旨在生成自然、真实的修复结果，同时保持身份一致性，推动感知质量与真实感的前沿进展，不限制计算资源或训练数据。评测采用加权图像质量评估（IQA）分数，并以AdaFace模型作为身份一致性检测工具。赛事吸引141人注册，13支团队提交有效模型，最终10支队伍获得正式评分。该协作项目显著提升了真实场景下人脸修复性能，并深入梳理了当前领域最新趋势。
原文摘要 · Abstract (English)
This paper provides a review of the NTIRE 2025 challenge on real-world face restoration, highlighting the proposed solutions and the resulting outcomes. The challenge focuses on generating natural, 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. The track of the challenge evaluates performance using a weighted image quality assessment (IQA) score and employs the AdaFace model as an identity checker. The competition attracted 141 registrants, with 13 teams submitting valid models, and ultimately, 10 teams achieved a valid score 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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