CVOct 15, 2025

NTIRE 2025 Challenge on Low Light Image Enhancement: Methods and Results

arXiv:2510.13670v123 citationsh-index: 982025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Originality Synthesis-oriented
AI Analysis

It addresses the problem of low-light image enhancement for computer vision applications, but is incremental as it summarizes a competition rather than introducing new methods.

This paper reviews the NTIRE 2025 Low-Light Image Enhancement Challenge, which aimed to identify effective networks for producing brighter and clearer images under challenging conditions, with 762 participants registering and 28 teams submitting valid entries.

This paper presents a comprehensive review of the NTIRE 2025 Low-Light Image Enhancement (LLIE) Challenge, highlighting the proposed solutions and final outcomes. The objective of the challenge is to identify effective networks capable of producing brighter, clearer, and visually compelling images under diverse and challenging conditions. A remarkable total of 762 participants registered for the competition, with 28 teams ultimately submitting valid entries. This paper thoroughly evaluates the state-of-the-art advancements in LLIE, showcasing the significant progress.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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