Image Generation On Stl 10
評価指標
FID
Inception score
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
比較表
モデル名 | FID | Inception score |
---|---|---|
transgan-two-transformers-can-make-one-strong | 18.28 | 10.43 |
dist-gan-an-improved-gan-using-distance | 36.19 | - |
spectral-normalization-for-generative | 40.1 | 9.10 |
wavelet-diffusion-models-are-fast-and | 12.93 | - |
enhancing-gans-with-mmd-neural-architecture | 11.61 | 11.79 |
dual-contradistinctive-generative-autoencoder-1 | 41.9 | 8.1 |
robust-diffusion-gan-using-semi-unbalanced | 11.5 | - |
autogan-neural-architecture-search-for | 31.01 | 9.16 |
peergan-generative-adversarial-networks-with | 51.37 | - |
robust-diffusion-gan-using-semi-unbalanced | 13.07 | - |
score-matching-model-for-unbounded-data-score-1 | 7.71 | 13.43 |
adaptive-weighted-discriminator-for-training | 34.72 | 9.61 |
enhancing-gan-performance-through-neural | 12.91 | 11.6 |
dual-discriminator-generative-adversarial | - | 7.98 |
discriminator-contrastive-divergence-semi | 22.25 | 9.25 |
quaternion-generative-adversarial-networks | 59.611 | 4.987 |
enhancing-gan-performance-through-neural | 14.84 | 11.66 |
eagan-efficient-two-stage-evolutionary | 23.34 | 10.02 |
enhancing-gans-with-mmd-neural-architecture | 13.07 | 11.85 |
discriminator-contrastive-divergence-semi | 17.68 | 9.33 |
diffusion-gan-training-gans-with-diffusion | 6.91 | - |
eagan-efficient-two-stage-evolutionary | 22.18 | 10.44 |
partition-guided-gans | 19.52 | 11.16 |
degas-differentiable-efficient-generator | 28.76 | 9.71 |
adaptive-weighted-discriminator-for-training | 26.32 | 9.59 |
diffusion-gan-training-gans-with-diffusion | 11.53 | - |
improving-mmd-gan-training-with-repulsive | 37.63 | 9.34 |
off-policy-reinforcement-learning-for | 25.35 | 9.51 |
styleformer-transformer-based-generative | 15.17 | 11.01 |
probgan-towards-probabilistic-gan-with | 46.74 | 8.87 |
enhancing-gan-performance-through-neural | 13.06 | 11.28 |