Image Generation On Celeba Hq 1024X1024
评估指标
FID
评测结果
各个模型在此基准测试上的表现结果
模型名称 | FID | Paper Title | Repository |
|---|---|---|---|
| Polarity-ProGAN | 7.28 | Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values | - |
| WaveDiff | 5.98 | Wavelet Diffusion Models are fast and scalable Image Generators | - |
| PG-SWGAN | 5.5 | Sliced Wasserstein Generative Models | - |
| HiT-B | 8.83 | Improved Transformer for High-Resolution GANs | - |
| PGGAN | 7.3 | Progressive Growing of GANs for Improved Quality, Stability, and Variation | - |
| Efficient-VDVAE | - | Efficient-VDVAE: Less is more | - |
| MSG-StyleGAN | 6.37 | MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks | - |
| StyleSwin | 4.43 | StyleSwin: Transformer-based GAN for High-resolution Image Generation | - |
| StyleGAN | 5.06 | A Style-Based Generator Architecture for Generative Adversarial Networks | - |
| COCO-GAN | 9.49 | COCO-GAN: Generation by Parts via Conditional Coordinating | - |
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