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cs.CV2025

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

Xiaoning Liu, Zongwei Wu, Florin-Alexandru Vasluianu +102

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…

cs.CV2025

Efficient Real-World Deblurring using Single Images: AIM 2025 Challenge Report

Daniel Feijoo, Paula Garrido-Mellado, Marcos V. Conde +4

This paper reviews the AIM 2025 Efficient Real-World Deblurring using Single Images Challenge, which aims to advance in efficient real-blur restoration. The challenge is based on a…

cs.CV2025

Towards Unified Image Deblurring using a Mixture-of-Experts Decoder

Daniel Feijoo, Paula Garrido-Mellado, Jaesung Rim +2

Image deblurring, removing blurring artifacts from images, is a fundamental task in computational photography and low-level computer vision. Existing approaches focus on specialize…

cs.CV2025

NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results

Xin Li, Yeying Jin, Xin Jin +134

This paper reviews the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images. This challenge received a wide range of impressive solutions, which are devel…

cs.CV2025

FLOL: Fast Baselines for Real-World Low-Light Enhancement

Juan C. Benito, Daniel Feijoo, Alvaro Garcia +1

Low-Light Image Enhancement (LLIE) is a key task in computational photography and imaging. The problem of enhancing images captured during night or in dark environments has been we…

cs.CV2024

DarkIR: Robust Low-Light Image Restoration

Daniel Feijoo, Juan C. Benito, Alvaro Garcia +1

Photography during night or in dark conditions typically suffers from noise, low light and blurring issues due to the dim environment and the common use of long exposure. Although…