NTIRE 2026 Challenge on Efficient Low Light Image Enhancement: Methods and Results

TL;DR

This paper reviews the NTIRE 2026 E-LLIE Challenge, showcasing recent lightweight methods for low-light image enhancement on mobile devices, with a focus on balancing quality and computational efficiency.

Contribution

It provides a systematic evaluation of challenge submissions, highlighting advancements in lightweight neural networks for low-light image enhancement.

Findings

Significant improvements in enhancement quality and efficiency achieved by challenge participants.

Diverse lightweight methods proposed for mobile low-light image enhancement.

Comprehensive overview of state-of-the-art progress in E-LLIE.

Abstract

This paper presents a comprehensive review of the NITRE 2026 Efficient Low Light Image Enhancement (E-LLIE) Challenge, highlighting the proposed solutions and final outcomes. This challenge focuses on mobile image enhancement under low-light conditions, aiming to design lightweight networks that improve enhancement quality while ensuring practical deployability under limited computational resources. A total of 207 participants registered, 27 teams submitted valid entries, and 17 teams ultimately provided valid factsheet. Based on these submissions, this paper provides a systematic evaluation of recent methods for E-LLIE, offering a comprehensive overview of state-of-the-art progress and demonstrating significant improvements in both performance and efficiency.