Papers › CURL: Neural Curve Layers for Global Image Enhancement
CURL: Neural Curve Layers for Global Image Enhancement
Sean Moran, Steven McDonagh, Gregory Slabaugh
We present a novel approach to adjust global image properties such as colour, saturation, and luminance using human-interpretable image enhancement curves, inspired by the Photoshop curves tool. Our method, dubbed neural CURve Layers (CURL), is designed as a multi-colour space neural retouching block trained jointly in three different colour spaces (HSV, CIELab, RGB) guided by a novel multi-colour space loss. The curves are fully differentiable and are trained end-to-end for different computer vision problems including photo enhancement (RGB-to-RGB) and as part of the image signal processing pipeline for image formation (RAW-to-RGB). To demonstrate the effectiveness of CURL we combine this global image transformation block with a pixel-level (local) image multi-scale encoder-decoder backbone network. In an extensive experimental evaluation we show that CURL produces state-of-the-art image quality versus recently proposed deep learning approaches in both objective and perceptual metrics, setting new state-of-the-art performance on multiple public datasets. Our code is publicly available at: https://github.com/sjmoran/CURL.
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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 |
|---|---|---|---|---|---|---|---|
| Image Enhancement | MIT-Adobe 5k | DIFAR (MSCA, level 1) | PSNR on proRGB | 24.2 | #10 of 11 | Archive leaderboard | report |
| Image Enhancement | MIT-Adobe 5k | DIFAR (MSCA, level 1) | SSIM on proRGB | 0.88 | #10 of 11 | Archive leaderboard | report |
| Photo Retouching | MIT-Adobe 5k | DIFAR (MSCA, level 1) | PSNR | 24.2 | #4 of 5 | Archive leaderboard | report |
| Photo Retouching | MIT-Adobe 5k | DIFAR (MSCA, level 1) | SSIM | 0.88 | #4 of 5 | 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.
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