CVApr 16

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

arXiv:2604.1455892.48 citationsh-index: 100
Predicted impact top 12% in CV · last 90 daysOriginality Synthesis-oriented
AI Analysis

This challenge benchmarks current super-resolution methods for the research community, but it is an incremental annual competition.

The NTIRE 2026 challenge on image super-resolution (×4) attracted 194 registrants and 31 valid submissions across two tracks (restoration and perceptual), providing a benchmark for recent methods. The best restoration track achieved a PSNR of 29.85 dB, while the perceptual track winner scored 3.45 in perceptual quality.

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.

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