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Found 3 papers, 3 papers with code
Robust Deep Ensemble Method for Real-world Image Denoising
In particular, we take well-trained CBDNet, NBNet, HINet, Uformer and GMSNet into denoiser pool, and a U-Net is adopted to predict pixel-wise weighting maps to fuse these denoisers.
Multi-level Wavelet Convolutional Neural Networks
Specifically, MWCNN for image restoration is based on U-Net architecture, and inverse wavelet transform (IWT) is deployed to reconstruct the high resolution (HR) feature maps.
Multi-level Wavelet-CNN for Image Restoration
With the modified U-Net architecture, wavelet transform is introduced to reduce the size of feature maps in the contracting subnetwork.
Ranked #2 on
Grayscale Image Denoising
on Set12 sigma25
