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Efficient Frequency Domain-Based Transformers for High-Quality Image Deblurring

CVPR 2023 · Image generation › Image restoration · approach: Image deblurring · 387 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use FFTformer instead of NAFNetImage deblurring · GoProPSNR: 33.71 -> 34.21Helped
Use FFTformer instead of Restormer-localImage deblurring · HIDEPSNR: 31.49 -> 31.62Helped
Use FFTformer instead of DeepRFT+Image deblurring · RealBlur-RPSNR: 39.84 -> 40.11Helped
Use FFTformer instead of StripformerImage deblurring · RealBlur-JPSNR: 32.48 -> 32.62Helped
Add FSAS to a model using only the original FFN (ablation)FFTformer · GoPro ablationPSNR: 33.19 -> 33.61Helped
Use DFFN instead of original FFN (ablation)Model using only the feed-forward component · GoPro ablationPSNR: 33.19 -> 33.55Helped
Use DFFN instead of original FFN (ablation)FSAS-based model · GoPro ablationPSNR: 33.61 -> 33.73Helped
Replace FSAS with shifted-window Swin attention (ablation)Model with DFFN · GoPro ablationPSNR: 33.46 -> 33.73Hurt
Use FSAS only in the decoder rather than in both encoder and decoder (ablation)FFTformer · GoPro asymmetric architecturePSNR: 33.56 -> 33.73Helped

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