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ShuffleMixer: An Efficient ConvNet for Image Super-Resolution

NeurIPS 2022 · Image generation › Super-resolution · approach: Perceptual and real-world SR · 72 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use channel splitting and shuffling for projection (ablation)ShuffleMixer baseline · DIV2K validation ×4PSNR: 29.96 -> 29.83Hurt
Repeat the CSS-based projection layer (ablation)ShuffleMixer baseline · DIV2K validation ×4PSNR: 29.83 -> 29.99Helped
Add a 3 × 3 convolution after every two shuffle mixer layers (ablation)CDC · DIV2K validation ×4PSNR: 29.99 -> 30.12Helped
Fuse input and output by summation, then apply a 3 × 3 convolution (ablation)CDC · DIV2K validation ×4PSNR: 29.99 -> 30.16Helped
Concatenate input and output, then apply a 3 × 3 convolution (ablation)CDC · DIV2K validation ×4PSNR: 29.99 -> 30.20Helped
Replace S-Conv with residual blocks (ablation)CDC · DIV2K validation ×4PSNR: 30.16 -> 30.24Helped
Replace S-Conv with Fused-MBConv (ablation)CDC · DIV2K validation ×4PSNR: 30.16 -> 30.21Helped
Increase depth-wise kernel size from 3 × 3 to 7 × 7 (ablation)ShuffleMixer · DIV2K validation ×4PSNR: 30.21 -> 30.28Helped
Increase depth-wise kernel size from 7 × 7 to 9 × 9 (ablation)ShuffleMixer · DIV2K validation ×4PSNR: 30.28 -> 30.29No clear effect
Increase depth-wise kernel size from 7 × 7 to 11 × 11 (ablation)ShuffleMixer · DIV2K validation ×4PSNR: 30.28 -> 30.28No clear effect
Increase depth-wise kernel size from 7 × 7 to 13 × 13 (ablation)ShuffleMixer · DIV2K validation ×4PSNR: 30.28 -> 30.29No clear effect

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