Image Generation On Fashion Mnist
평가 지표
FID
Precision
Recall
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | FID | Precision | Recall | Paper Title | Repository |
|---|---|---|---|---|---|
| PR-GLOW- Precision | 83.25 | 0.73 | 0.34 | - | - |
| GLF+perceptual loss (ours) | 10.3 | - | - | Generative Latent Flow | |
| PR-GLOW- Recall | 42.85 | 0.6648 | 0.4973 | - | - |
| PAE | 28.0 | - | - | Probabilistic Autoencoder | |
| Spiking-Diffusion | 91.98 | - | - | Spiking-Diffusion: Vector Quantized Discrete Diffusion Model with Spiking Neural Networks | |
| PeerGAN | 21.73 | - | - | DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN Training | - |
| Sliced Iterative Generator | 13.7 | - | - | Sliced Iterative Normalizing Flows |
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