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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 151–200 of 316 papers

TitleStatusHype
Brighten-and-Colorize: A Decoupled Network for Customized Low-Light Image Enhancement—0
Dual Degradation-Inspired Deep Unfolding Network for Low-Light Image Enhancement—0
Decomposition Ascribed Synergistic Learning for Unified Image Restoration—0
Towards General Low-Light Raw Noise Synthesis and ModelingCode1
From Generation to Suppression: Towards Effective Irregular Glow Removal for Nighttime Visibility EnhancementCode1
LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image EnhancementCode1
Lighting up NeRF via Unsupervised Decomposition and EnhancementCode1
Division Gets Better: Learning Brightness-Aware and Detail-Sensitive Representations for Low-Light Image Enhancement—0
ExposureDiffusion: Learning to Expose for Low-light Image EnhancementCode1
Glow in the Dark: Low-Light Image Enhancement with External MemoryCode1
Enhancing Low-Light Images Using Infrared-Encoded Images—0
LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse DiffusionCode1
A ground-based dataset and a diffusion model for on-orbit low-light image enhancement—0
ProRes: Exploring Degradation-aware Visual Prompt for Universal Image RestorationCode1
Enlighten Anything: When Segment Anything Model Meets Low-Light Image EnhancementCode1
LUT-GCE: Lookup Table Global Curve Estimation for Fast Low-light Image Enhancement—0
Unsupervised Low Light Image Enhancement Using SNR-Aware Swin Transformer—0
Bilevel Fast Scene Adaptation for Low-Light Image EnhancementCode1
Low-Light Image Enhancement with Wavelet-based Diffusion ModelsCode2
Make Lossy Compression Meaningful for Low-Light ImagesCode0
Learning a Single Convolutional Layer Model for Low Light Image Enhancement—0
FLIGHT Mode On: A Feather-Light Network for Low-Light Image EnhancementCode1
Advancing Unsupervised Low-light Image Enhancement: Noise Estimation, Illumination Interpolation, and Self-RegulationCode0
Pyramid Diffusion Models For Low-light Image EnhancementCode1
SCRNet: a Retinex Structure-based Low-light Enhancement Model Guided by Spatial Consistency—0
Low-Light Image Enhancement via Structure Modeling and GuidanceCode2
ALL-E: Aesthetics-guided Low-light Image Enhancement—0
Learning Semantic-Aware Knowledge Guidance for Low-Light Image EnhancementCode2
Simplifying Low-Light Image Enhancement Networks with Relative Loss FunctionsCode1
Random Weights Networks Work as Loss Prior Constraint for Image Restoration—0
Few-Shot Domain Adaptation for Low Light RAW Image EnhancementCode1
Neural Preset for Color Style TransferCode2
Low-Light Image Enhancement by Learning Contrastive Representations in Spatial and Frequency Domains—0
Implicit Neural Representation for Cooperative Low-light Image EnhancementCode2
Denoising Diffusion Post-Processing for Low-Light Image EnhancementCode1
Retinexformer: One-stage Retinex-based Transformer for Low-light Image EnhancementCode5
Aleth-NeRF: Low-light Condition View Synthesis with Concealing FieldsCode1
CUR Transformer: A Convolutional Unbiased Regional Transformer for Image DenoisingCode0
Embedding Fourier for Ultra-High-Definition Low-Light Image Enhancement—0
Gap-closing Matters: Perceptual Quality Evaluation and Optimization of Low-Light Image EnhancementCode1
Low-Light Image Enhancement with Multi-Stage Residue Quantization and Brightness-Aware AttentionCode1
Learning a Simple Low-Light Image Enhancer From Paired Low-Light InstancesCode1
DNF: Decouple and Feedback Network for Seeing in the DarkCode1
You Do Not Need Additional Priors or Regularizers in Retinex-Based Low-Light Image Enhancement—0
Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based MethodCode2
SALVE: Self-supervised Adaptive Low-light Video Enhancement—0
Low-Light Image and Video Enhancement: A Comprehensive Survey and BeyondCode0
On the Robustness of Normalizing Flows for Inverse Problems in Imaging—0
SLLEN: Semantic-aware Low-light Image Enhancement Network—0
Learning to Kindle the StarlightCode0
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