The Fourth Challenge on Image Super-Resolution ($\times$4) at NTIRE 2026: Benchmark Results and Method Overview

TL;DR

The NTIRE 2026 challenge on image super-resolution ($\times$4) at CVPR 2026 benchmarks recent methods, introduces two evaluation tracks, and analyzes participant solutions to advance the field.

Contribution

This paper presents the design, datasets, evaluation protocols, and results of the NTIRE 2026 super-resolution challenge, highlighting recent advances and future directions.

Findings

194 participants registered, 31 teams submitted entries

Two evaluation tracks: fidelity (PSNR) and perceptual quality

Summarizes top methods and challenge insights

Abstract

This paper presents the NTIRE 2026 image super-resolution ($\times$4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to reconstruct high-resolution (HR) images from low-resolution (LR) inputs generated through bicubic downsampling with a $\times$4 scaling factor. The objective is to develop effective super-resolution solutions and analyze recent advances in the field. To reflect the evolving objectives of image super-resolution, the challenge includes two tracks: (1) a restoration track, which emphasizes pixel-wise fidelity and ranks submissions based on PSNR; and (2) a perceptual track, which focuses on visual realism and evaluates results using a perceptual score. A total of 194 participants registered for the challenge, with 31 teams submitting valid entries. This report summarizes the challenge design, datasets, evaluation protocol, main results, and methods of participating teams. The challenge provides a unified benchmark and offers insights into current progress and future directions in image super-resolution.