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Residual Multiplicative Filter Networks for Multiscale Reconstruction

NeurIPS 2022 · 3D vision › Face and shape · approach: Implicit neural representation design · 8 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Add residual connections to staged Bacon (ablation)Bacon · Natural images, scale 3Mean absolute Fourier spectrum difference: 17.97 $\pm$ 4.27 -> 9.23 $\pm$ 2.73Helped
Add the proposed frequency initialization to residual Bacon (ablation)Residual MFN · Natural images, scale 3Mean absolute Fourier spectrum difference: 9.23 $\pm$ 2.73 -> 4.32 $\pm$ 1.35Helped
Add residual connections and proposed frequency initializationBacon · Natural images, image generalizationPSNR (dB): 28.46 $\pm$ 3.61 -> 28.33 $\pm$ 4.42No clear effect
Add residual connections to staged Bacon (ablation)Bacon · Text images, scale 3Mean absolute Fourier spectrum difference: 13.79 $\pm$ 4.60 -> 8.11 $\pm$ 2.60Helped
Add the proposed frequency initialization to residual Bacon (ablation)Residual MFN · Text images, scale 3Mean absolute Fourier spectrum difference: 8.11 $\pm$ 2.60 -> 3.56 $\pm$ 1.16Helped
Add residual connections and proposed frequency initializationBacon · Text images, image generalizationPSNR (dB): 31.57 $\pm$ 2.29 -> 32.04 $\pm$ 2.34Helped
Train with coarse-to-fine stages rather than supervising only the full-scale reconstruction (ablation)Residual MFN cryo-EM reconstruction · Synthetic cryo-EM reconstructionStructure reconstruction / pose optimizationHelped
Use λ₂ = 2 and λ₁ = 0.3 rather than the other investigated λ settings (ablation)Residual MFN · Image fitting and cryo-EM reconstructionTest loss / FSCHelped

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