Low Light Image Enhancement Challenge at NTIRE 2026

TL;DR

This paper reviews the NTIRE 2026 Low Light Image Enhancement Challenge, showcasing advancements in networks that improve image clarity in low-light conditions using a novel dataset.

Contribution

It provides a comprehensive overview of challenge solutions, results, and progress in low-light image enhancement with a new dataset and evaluation of state-of-the-art methods.

Findings

Significant progress in low-light image enhancement techniques.

High participation indicates growing interest and research activity.

Evaluation of methods demonstrates effectiveness of recent approaches.

Abstract

This paper presents a comprehensive review of the NTIRE 2026 Low Light Image Enhancement Challenge, highlighting the proposed solutions and final results. The objective of this challenge is to identify effective networks capable of producing clearer and visually compelling images in diverse and challenging conditions by learning representative visual cues with the purpose of restoring information loss due to low-contrast and noisy images. A total of 195 participants registered for the first track and 153 for the second track of the competition, and 22 teams ultimately submitted valid entries. This paper thoroughly evaluates the state-of-the-art advances in (joint denoising and) low-light image enhancement, showcasing the significant progress in the field, while leveraging samples of our novel dataset.