Image Generation On Lsun Cat 256 X 256
평가 지표
FID
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | FID | Paper Title | Repository |
|---|---|---|---|
| Projected GAN | 3.89 | Projected GANs Converge Faster | |
| Polarity-StyleGAN2 | 6.34 | Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values | |
| StyleGAN | - | A Style-Based Generator Architecture for Generative Adversarial Networks | |
| PGGAN | 37.52 | Progressive Growing of GANs for Improved Quality, Stability, and Variation | |
| StyleGAN2 | 6.93 | Analyzing and Improving the Image Quality of StyleGAN | |
| Denoising Diffusion Probabilistic Model | 19.75 | Denoising Diffusion Probabilistic Models | |
| ADM (dropout) | 5.57 | Diffusion Models Beat GANs on Image Synthesis | |
| Vision-aided GAN | 3.87 | Ensembling Off-the-shelf Models for GAN Training |
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