Conditional Image Generation On Imagenet

Metrics

FID

Inception score

Results

Performance results of various models on this benchmark

			Paper Title
Projection Discriminator	27.62	36.8	cGANs with Projection Discriminator
SAGAN	18.65	52.52	Self-Attention Generative Adversarial Networks
Your Local GAN	15.94	57.22	Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models
HamGAN	14.80	58.75	Is Attention Better Than Matrix Decomposition?
FQ-GAN	13.77	54.36	Feature Quantization Improves GAN Training
BigGAN + instance selection	9.61	114.32	Instance Selection for GANs
IC-GAN + DA	9.5	108.6	Instance-Conditioned GAN
BigGAN	8.7	98.8	Large Scale GAN Training for High Fidelity Natural Image Synthesis
Omni-GAN	8.30	190.94	Omni-GAN: On the Secrets of cGANs and Beyond
ReACGAN	8.206	96.299	Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training
ADC-GAN	8.02	108.10	Conditional GANs with Auxiliary Discriminative Classifier
S3 GAN	7.7	83.1	High-Fidelity Image Generation With Fewer Labels
CR-BigGAN	6.66	-	Consistency Regularization for Generative Adversarial Networks
Omni-INR-GAN	6.53	262.85	Omni-GAN: On the Secrets of cGANs and Beyond
BigGAN-deep	5.7	124.5	Large Scale GAN Training for High Fidelity Natural Image Synthesis
simple diffusion (U-ViT, L)	3.23	171.9	Simple diffusion: End-to-end diffusion for high resolution images
ADM-G (classifier_scale=0.5)	2.97	-	Diffusion Models Beat GANs on Image Synthesis
simple diffusion (U-Net)	2.88	137.3	Simple diffusion: End-to-end diffusion for high resolution images
ADM-G + EDS + ECT (ED-DPM, classifier_scale=0.6)	2.68	169.24	Entropy-driven Sampling and Training Scheme for Conditional Diffusion Generation
ADM-G + EDS (ED-DPM, classifier_scale=0.4)	2.63	159.72	Entropy-driven Sampling and Training Scheme for Conditional Diffusion Generation

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Conditional Image Generation On Imagenet

Metrics

Results

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Conditional Image Generation On Imagenet

Metrics

Results