Low Light Image Enhancement Challenge at NTIRE 2026
cs.CV
/ Authors
George Ciubotariu, Sharif S M A, Abdur Rehman, Fayaz Ali Dharejo, Rizwan Ali Naqvi, Marcos V. Conde, Radu Timofte, Zhi Jin, Hongjun Wu, Wenjian Zhang
and 81 more authors
Chang Ye, Xunpeng Yi, Qinglong Yan, Yibing Zhang, Nikhil Akalwadi, Varda I Pattanshetty, Varsha I Pattanshetty, Padmashree Desai, Uma Mudenagudi, Ramesh Ashok Tabib, Hao Yang, Ruikun Zhang, Liyuan Pan, Furkan Kınlı, Donghun Ryou, Inju Ha, Junoh Kang, Bohyung Han, Wei Zhou, Yuval Haitman, Ariel Lapid, Reuven Peretz, Idit Diamant
/ 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.