CVMay 4

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

arXiv:2605.0221285.5
Predicted impact top 21% in CV · last 90 daysOriginality Synthesis-oriented
AI Analysis

This challenge provides a benchmark and overview of state-of-the-art methods for efficient low-light image enhancement on mobile devices, but is incremental as it primarily surveys existing approaches.

The NTIRE 2026 Efficient Low Light Image Enhancement Challenge attracted 207 registrations, with 27 valid submissions, and demonstrated significant improvements in both enhancement quality and computational efficiency for mobile deployment.

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.

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