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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 71–80 of 316 papers

TitleStatusHype
Unrolled Decomposed Unpaired Learning for Controllable Low-Light Video EnhancementCode1
SDI-Net: Toward Sufficient Dual-View Interaction for Low-light Stereo Image Enhancement—0
ExpoMamba: Exploiting Frequency SSM Blocks for Efficient and Effective Image EnhancementCode1
Latent Disentanglement for Low Light Image Enhancement—0
Wave-Mamba: Wavelet State Space Model for Ultra-High-Definition Low-Light Image EnhancementCode2
ALEN: A Dual-Approach for Uniform and Non-Uniform Low-Light Image EnhancementCode0
RestoreAgent: Autonomous Image Restoration Agent via Multimodal Large Language Models—0
Dual High-Order Total Variation Model for Underwater Image RestorationCode0
AGLLDiff: Guiding Diffusion Models Towards Unsupervised Training-free Real-world Low-light Image Enhancement—0
GLARE: Low Light Image Enhancement via Generative Latent Feature based Codebook RetrievalCode2
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