Papers › GLARE: Low Light Image Enhancement via Generative Latent Feature based Codebook Retrieval
GLARE: Low Light Image Enhancement via Generative Latent Feature based Codebook Retrieval
Han Zhou, Wei Dong, Xiaohong Liu, Shuaicheng Liu, Xiongkuo Min, Guangtao Zhai, Jun Chen
Most existing Low-light Image Enhancement (LLIE) methods either directly map Low-Light (LL) to Normal-Light (NL) images or use semantic or illumination maps as guides. However, the ill-posed nature of LLIE and the difficulty of semantic retrieval from impaired inputs limit these methods, especially in extremely low-light conditions. To address this issue, we present a new LLIE network via Generative LAtent feature based codebook REtrieval (GLARE), in which the codebook prior is derived from undegraded NL images using a Vector Quantization (VQ) strategy. More importantly, we develop a generative Invertible Latent Normalizing Flow (I-LNF) module to align the LL feature distribution to NL latent representations, guaranteeing the correct code retrieval in the codebook. In addition, a novel Adaptive Feature Transformation (AFT) module, featuring an adjustable function for users and comprising an Adaptive Mix-up Block (AMB) along with a dual-decoder architecture, is devised to further enhance fidelity while preserving the realistic details provided by codebook prior. Extensive experiments confirm the superior performance of GLARE on various benchmark datasets and real-world data. Its effectiveness as a preprocessing tool in low-light object detection tasks further validates GLARE for high-level vision applications. Code is released at https://github.com/LowLevelAI/GLARE.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Low-Light Image Enhancement | LOL | GLARE | Average PSNR | 27.35 | #5 of 40 | Archive leaderboard | report |
| Low-Light Image Enhancement | LOL | GLARE | LPIPS | 0.083 | #5 of 40 | Archive leaderboard | report |
| Low-Light Image Enhancement | LOL | GLARE | SSIM | 0.883 | #5 of 40 | Archive leaderboard | report |
| Low-Light Image Enhancement | LOL | GLARE | SSIM (sRGB) | 0.883 | #5 of 40 | Archive leaderboard | report |
| Low-Light Image Enhancement | LOLv2 | GLARE | Average PSNR | 28.98 | #2 of 12 | Archive leaderboard | report |
| Low-Light Image Enhancement | LOLv2 | GLARE | LPIPS | 0.097 | #2 of 12 | Archive leaderboard | report |
| Low-Light Image Enhancement | LOLv2 | GLARE | SSIM | 0.905 | #2 of 12 | Archive leaderboard | report |
| Low-Light Image Enhancement | LOLv2-synthetic | GLARE | Average PSNR | 29.84 | #2 of 9 | Archive leaderboard | report |
| Low-Light Image Enhancement | LOLv2-synthetic | GLARE | SSIM | 0.958 | #2 of 9 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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