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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