NPPE-3 Low-Light Denoise + 4x Super-Resolution
RRDB backbone (10 blocks, 64 features, growth channels=32), scale x4.
Input: RGB noisy low-resolution image. Output: grayscale HR luminance.
The competition score uses grayscale output and every 8th column. The model was trained with MSE loss to align optimization with PSNR.
Training:
- iterations: 12000
- patch size: 64
- optimizer: Adam
- scheduler: cosine annealing
- learning rate: 0.0002
The final leaderboard-exact validation PSNR is printed by Cell 6.
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