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Adversarial Fisher Vectors for Unsupervised Representation Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use AFVs instead of pooled discriminator features (ablation) | GAN discriminator features · CIFAR10 | classification accuracy: 65.3 -> 86.2 | Helped |
| Add data augmentation during GAN training (ablation) | AFV-128-50000 · CIFAR10 | classification accuracy: 86.2 -> 87.1 | Helped |
| Increase model channel size to 256 (ablation) | AFV-128-50000 + augment · CIFAR10 | classification accuracy: 87.1 -> 88.5 | Helped |
| Add CIFAR100 training data (ablation) | AFV-256-50000 + augment · CIFAR10 | classification accuracy: 88.5 -> 89.1 | Helped |
| Add CIFAR100 training data (ablation) | AFV-256-50000 + augment · CIFAR100 | classification accuracy | Helped |
| Use AFV as the perceptual similarity metric | ImageNet-trained GAN · BAPPS traditional distortions | 2AFC: 70.6 -> 74.9 | Helped |
| Use AFV as the perceptual similarity metric | ImageNet-trained GAN · BAPPS CNN distortions | 2AFC: 83.1 -> 80.2 | Hurt |
| Use AFV as the perceptual similarity metric | ImageNet-trained GAN · BAPPS average | Avg 2AFC: 78.0 -> 77.6 | Hurt |
| Use AFV as the perceptual similarity metric | ImageNet-trained GAN · BAPPS traditional distortions | JND: 44.0 -> 55.7 | Helped |
| Use AFV as the perceptual similarity metric | ImageNet-trained GAN · BAPPS CNN distortions | JND: 67.6 -> 62.0 | Hurt |
| Use AFV as the perceptual similarity metric | ImageNet-trained GAN · BAPPS average | Avg JND: 55.6 -> 58.9 | Helped |
| Constrain generator updates to be local with the MCMC-inspired objective (ablation) | GAN generator · ImageNet 64x64 | Inception Score | Helped |
Closest papers by meaning
- Fisher GAN (NeurIPS 2017 · similarity 0.90)
- Scalable Energy-Based Models via Adversarial Training: Unifying Discrimination and Generation (ICLR 2026 · similarity 0.88)
- Calibrating Energy-based Generative Adversarial Networks (ICLR 2017 · similarity 0.87)
- Energy-based Generative Adversarial Networks (ICLR 2017 · similarity 0.87)
- Structure-preserving GANs (ICML 2022 · similarity 0.87)
- Improving Adversarial Energy-Based Model via Diffusion Process (ICML 2024 · similarity 0.86)
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