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Slimmable Generative Adversarial Networks

AAAI 2021 · Image generation › GANs · approach: GAN latent optimization and evaluation · 25 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace independently trained width-specific generators with a slimmable generatorDCGAN · CIFAR-10FID at 0.25× width: 46.9 -> 37.3Helped
Replace independently trained width-specific generators with a slimmable generatorResNet · STL-10FID at 0.25× width: 66.6 -> 69.1Hurt
Use sliceable conditional batch normalization instead of naive conditional batch normalizationSlimmable cGAN-pd · CIFAR-10FID at 0.25× width: 21.7 -> 19.5Helped
Use sliceable conditional batch normalization instead of naive conditional batch normalizationSlimmable cGAN-pd · CIFAR-100FID at 0.25× width: 26.8 -> 23.8Helped
Add stepwise inplace distillation (ablation)SlimDCGAN · CIFAR-10mIC: 282.7 -> 231.3Helped
Add stepwise inplace distillation (ablation)SlimResGAN · STL-10mIC: 342.4 -> 248.7Helped
Share partial parameters across discriminators (ablation)Slimmable G · CIFAR-10FID AVG: 35.8 -> 30.8Helped
Add stepwise inplace distillation to shared-discriminator SlimGAN (ablation)DCGAN · CIFAR-10FID AVG: 30.8 -> 29.2Helped
Use one discriminator for all generator widths (ablation)Slimmable generator · CIFAR-10FID AVG: 30.8 -> 154.3Hurt
Make the discriminator slimmable rather than sharing partial discriminator parameters (ablation)Slimmable generator · CIFAR-10FID AVG: 30.8 -> 35.9Hurt
Remove adversarial loss for narrow generators (ablation)SlimGAN · CIFAR-10FID AVG: 29.2 -> 52.7Hurt
Distill all narrow generators directly from the widest generator rather than stepwise (ablation)SlimGAN · CIFAR-10FID AVG: 29.2 -> 29.6No clear effect

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