Image Generation On Stl 10

Metrics

FID

Inception score

Results

Performance results of various models on this benchmark

Comparison Table

Model Name	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