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AdaptiveMix: Improving GAN Training via Feature Space Shrinkage
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add AdaptiveMix to WGAN training | WGAN · CIFAR-10 | Min FID: 55.96 -> 30.85 | Helped |
| Add AdaptiveMix to StyleGAN-V2 | StyleGAN-V2 · AFHQ-Cat-5k | FID: 7.737 -> 4.477 | Helped |
| Add AdaptiveMix to APA | APA with StyleGAN-V2 · AFHQ-Cat-5k | FID: 4.876 -> 4.148 | Helped |
| Add AdaptiveMix to StyleGAN-V2 | StyleGAN-V2 · FFHQ-5k | FID: 37.830 -> 18.769 | Helped |
| Add AdaptiveMix to APA | APA with StyleGAN-V2 · FFHQ-5k | FID: 13.249 -> 11.498 | Helped |
| Add AdaptiveMix to DCGAN's WGAN objective | DCGAN · CelebA | FID: 23.51 -> 12.43 | Helped |
| Add AdaptiveMix to image classification | WRN-28-10 · CIFAR-10 | accuracy: 96.11 -> 96.80 | Helped |
| Add AdaptiveMix to image classification | PreActResNet-18 · Tiny-ImageNet | accuracy: 57.23 -> 60.59 | Helped |
| Add AdaptiveMix to 1DS without Monte Carlo sampling | 1DS w/o MC · CIFAR-10 / TIN-C | F1 score: 0.890 -> 0.922 | Helped |
| Set the mixing Beta-distribution parameter α to 2.0 instead of 1.0 (ablation) | AdaptiveMix with WRN-28-10 · CIFAR-10 | accuracy (FGSM 8/255): 74.18 -> 71.27 | Hurt |
| Add AdaptiveMix to APA with StyleGAN-V2 | APA · FFHQ (Full) | FID: 3.678 -> 3.609 | Helped |
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- RG-GAN: Dynamic Regenerative Pruning for Data-Efficient Generative Adversarial Networks (AAAI 2024 · similarity 0.88)
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- Revisiting Adversarial Training at Scale (CVPR 2024 · similarity 0.88)
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