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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

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Showing 101–125 of 316 papers

TitleStatusHype
CodeEnhance: A Codebook-Driven Approach for Low-Light Image Enhancement—0
DI-Retinex: Digital-Imaging Retinex Theory for Low-Light Image Enhancement—0
Towards Robust Event-guided Low-Light Image Enhancement: A Large-Scale Real-World Event-Image Dataset and Novel Approach—0
AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and ModulationCode3
Zero-LED: Zero-Reference Lighting Estimation Diffusion Model for Low-Light Image Enhancement—0
Edge-guided Low-light Image Enhancement with Inertial Bregman Alternating Linearized Minimization—0
A Lightweight Low-Light Image Enhancement Network via Channel Prior and Gamma Correction—0
Seed Optimization with Frozen Generator for Superior Zero-shot Low-light Enhancement—0
You Only Need One Color Space: An Efficient Network for Low-light Image EnhancementCode4
Troublemaker Learning for Low-Light Image EnhancementCode1
InstructIR: High-Quality Image Restoration Following Human InstructionsCode4
LYT-NET: Lightweight YUV Transformer-based Network for Low-light Image EnhancementCode2
Edge-Computing-Enabled Deep Learning Approach for Low-Light Satellite Image EnhancementCode0
MixNet: Efficient Global Modeling for Ultra-High-Definition Image RestorationCode0
PPformer: Using pixel-wise and patch-wise cross-attention for low-light image enhancementCode1
Low-light Image Enhancement via CLIP-Fourier Guided Wavelet DiffusionCode2
A Non-Uniform Low-Light Image Enhancement Method with Multi-Scale Attention Transformer and Luminance Consistency LossCode0
Revealing Shadows: Low-Light Image Enhancement Using Self-Calibrated Illumination—0
JoReS-Diff: Joint Retinex and Semantic Priors in Diffusion Model for Low-light Image Enhancement—0
ClassLIE: Structure- and Illumination-Adaptive Classification for Low-Light Image Enhancement—0
Enlighten-Your-Voice: When Multimodal Meets Zero-shot Low-light Image EnhancementCode0
DiffuseRAW: End-to-End Generative RAW Image Processing for Low-Light Images—0
Learning to See Low-Light Images via Feature Domain Adaptation—0
LDM-ISP: Enhancing Neural ISP for Low Light with Latent Diffusion Models—0
Resfusion: Denoising Diffusion Probabilistic Models for Image Restoration Based on Prior Residual NoiseCode1
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