NTIRE 2024 challenge on low light image enhancement: Methods and results

X Liu, Z Wu, A Li, FA Vasluianu, Y Zhang, S Gu… - arXiv preprint arXiv …, 2024 - arxiv.org
This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting
the proposed solutions and results. The aim of this challenge is to discover an effective …

DiffLight: Integrating Content and Detail for Low-light Image Enhancement

Y Feng, S Hou, H Lin, Y Zhu, P Wu… - Proceedings of the …, 2024 - openaccess.thecvf.com
Abstract The Low Light Image Enhancement (LLIE) task has been a hotspot in low-level
computer vision research. The camera sensor can only capture a small amount of ambient …

You only need one color space: An efficient network for low-light image enhancement

Q Yan, Y Feng, C Zhang, P Wang, P Wu… - arXiv preprint arXiv …, 2024 - arxiv.org
Low-Light Image Enhancement (LLIE) task tends to restore the details and visual information
from corrupted low-light images. Most existing methods learn the mapping function between …

[HTML][HTML] A comprehensive study of object tracking in low-light environments

A Yi, N Anantrasirichai - Sensors, 2024 - mdpi.com
Accurate object tracking in low-light environments is crucial, particularly in surveillance,
ethology applications, and biometric recognition systems. However, achieving this is …

[HTML][HTML] Denoising diffusion post-processing for low-light image enhancement

S Panagiotou, AS Bosman - Pattern Recognition, 2024 - Elsevier
Low-light image enhancement (LLIE) techniques attempt to increase the visibility of images
captured in low-light scenarios. However, as a result of enhancement, a variety of image …

Lightendiffusion: Unsupervised low-light image enhancement with latent-retinex diffusion models

H Jiang, A Luo, X Liu, S Han, S Liu - arXiv preprint arXiv:2407.08939, 2024 - arxiv.org
In this paper, we propose a diffusion-based unsupervised framework that incorporates
physically explainable Retinex theory with diffusion models for low-light image …

Low-Light Image Enhancement Framework for Improved Object Detection in Fisheye Lens Datasets

DQ Tran, A Aboah, Y Jeon… - Proceedings of the …, 2024 - openaccess.thecvf.com
This study addresses the evolving challenges in urban traffic monitoring detection systems
based on fisheye lens cameras by proposing a framework that improves the efficacy and …

Image all-in-one adverse weather removal via dynamic model weights generation

Y Wan, M Shao, Y Cheng, W Zuo - Knowledge-Based Systems, 2024 - Elsevier
Restoring image under multiple weather conditions in an all-in-one fashion remains a
formidable challenge due to images captured under different weather conditions exhibit …

Unveiling Advanced Frequency Disentanglement Paradigm for Low-Light Image Enhancement

K Zhou, X Lin, W Li, X Xu, Y Cai, Z Liu, X Han… - European Conference on …, 2025 - Springer
Previous low-light image enhancement (LLIE) approaches, while employing frequency
decomposition techniques to address the intertwined challenges of low frequency (eg …

MixNet: Towards Effective and Efficient UHD Low-Light Image Enhancement

C Wu, Z Zheng, X Jia, W Ren - arXiv preprint arXiv:2401.10666, 2024 - arxiv.org
With the continuous advancement of imaging devices, the prevalence of Ultra-High-
Definition (UHD) images is rising. Although many image restoration methods have achieved …