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Low-Light Image Enhancement

Low-Light Image Enhancement is a computer vision task that involves improving the quality of images captured under low-light conditions. The goal of low-light image enhancement is to make images brighter, clearer, and more visually appealing, without introducing too much noise or distortion.

Papers

Showing 126150 of 316 papers

TitleStatusHype
Image Demoireing with Learnable Bandpass FiltersCode1
Illumination-Aware Image Quality Assessment for Enhanced Low-light ImageCode1
Illuminating Darkness: Enhancing Real-world Low-light Scenes with Smartphone ImagesCode1
IceNet for Interactive Contrast EnhancementCode1
HVI-CIDNet+: Beyond Extreme Darkness for Low-Light Image EnhancementCode1
Abandoning the Bayer-Filter to See in the DarkCode1
See through the Dark: Learning Illumination-affined Representations for Nighttime Occupancy PredictionCode1
Degrade is Upgrade: Learning Degradation for Low-light Image EnhancementCode1
Semi-LLIE: Semi-supervised Contrastive Learning with Mamba-based Low-light Image EnhancementCode1
Unified Image Restoration and Enhancement: Degradation Calibrated Cycle Reconstruction Diffusion ModelCode1
Zero-Shot Low-Light Image Enhancement via Joint Frequency Domain Priors Guided DiffusionCode1
Deep Retinex Decomposition for Low-Light EnhancementCode0
HiLLIE: Human-in-the-Loop Training for Low-Light Image EnhancementCode0
Rethinking the Atmospheric Scattering-driven Attention via Channel and Gamma Correction Priors for Low-Light Image EnhancementCode0
Bilateral Interaction for Local-Global Collaborative Perception in Low-Light Image EnhancementCode0
Restoring Extremely Dark Images in Real TimeCode0
Extremely Low-light Image Enhancement with Scene Text RestorationCode0
ALEN: A Dual-Approach for Uniform and Non-Uniform Low-Light Image EnhancementCode0
Attention Guided Low-light Image Enhancement with a Large Scale Low-light Simulation DatasetCode0
CUR Transformer: A Convolutional Unbiased Regional Transformer for Image DenoisingCode0
ERetinex: Event Camera Meets Retinex Theory for Low-Light Image EnhancementCode0
Low-light Image Enhancement Using the Cell Vibration ModelCode0
Enlighten-Your-Voice: When Multimodal Meets Zero-shot Low-light Image EnhancementCode0
RCNet: Deep Recurrent Collaborative Network for Multi-View Low-Light Image EnhancementCode0
Enhancing Low-Light Images with Kolmogorov–Arnold Networks in Transformer AttentionCode0
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