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Research map / Image generation / Editing and style transfer

Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes

CVPR 2021 · Image generation › Editing and style transfer · approach: Arbitrary neural style transfer · 68 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Optimize parameterized brushstrokes instead of pixelsGatys-style artistic style transfer · 8 stylesmean deception score: 0.389 -> 0.588Helped
Optimize parameterized brushstrokes instead of pixelsGatys-style artistic style transfer · 8 stylesmean human deception rate: 0.139 -> 0.268Helped
Optimize parameterized brushstrokes instead of pixelsartistic style transfer · 8 stylesmean deception score: 0.451 -> 0.588Helped
Optimize parameterized brushstrokes instead of pixelsartistic style transfer · 8 stylesmean human deception rate: 0.146 -> 0.268Helped
Use the explicit differentiable renderer instead of the trained renderer (ablation)brushstroke rendering · brushstroke generationmemory useHelped
Use the explicit differentiable renderer instead of the trained renderer (ablation)brushstroke rendering · brushstroke generationrendering speedMixed
Use the explicit differentiable renderer instead of Learning to Paintimage reconstruction · CelebA, 200 strokesMSE: 20% lowerHelped
Use the explicit differentiable renderer instead of Learning to Paintimage reconstruction · CelebA, 1000 strokesMSE: 49% lowerHelped
Increase the number of brushstrokes from 1K to 20K (ablation)explicit brushstroke renderer · renderer runtimespeed: 1.17 $\pm$ 0.01 -> 0.93 $\pm$ 0.01Hurt

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