CVApr 19

The First Challenge on Mobile Real-World Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

arXiv:2604.173060.3411 citationsh-index: 100
AI Analysis15

This challenge benchmarks and advances mobile real-world image super-resolution for practitioners needing efficient, high-quality models on resource-constrained devices.

The NTIRE 2026 challenge on mobile real-world image super-resolution aimed to recover high-resolution images from low-resolution inputs with unknown degradations and a x4 scaling factor, while ensuring models are executable on mobile devices. The challenge attracted 108 registrants, with 16 teams achieving valid scores, advancing mobile super-resolution performance.

This paper provides a review of the NTIRE 2026 challenge on mobile real-world image super-resolution, highlighting the proposed solutions and the resulting outcomes. The challenge aims to recover high-resolution (HR) images from low-resolution (LR) counterparts generated through unknown degradations with a x4 scaling factor while ensuring the models remain executable on mobile devices. The objective is to develop effective and efficient network designs or solutions that achieve state-of-the-art real-world image super-resolution performance. The track of the challenge evaluates performance using a weighted combination of image quality assessment (IQA) score and speedup ratios. The competition attracted 108 registrants, with 16 teams achieving a valid score in the final ranking. This collaborative effort advances the performance of mobile real-world image super-resolution while offering an in-depth overview of the latest trends in the field.

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