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

arXiv:2604.10532v1 Announce Type: new 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.

Related

• SMFD-UNet: Semantic Face Mask Is The Only Thing You Need To Deblur Faces
• NTIRE 2026 Challenge on Bitstream-Corrupted Video Restoration: Methods and Results
• NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
• NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models: Datasets, Methods and Results
• NTIRE 2026 Challenge on Single Image Reflection Removal in the Wild: Datasets, Results, and Methods
• NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild

Source: arXiv cs.CV | 2026-04-14