Image Generation On Imagenet 128X128

FID

Results

Performance results of various models on this benchmark

		Paper Title
SS-GAN (sBN)	43.87	Self-Supervised GANs via Auxiliary Rotation Loss
HiT	30.83	Improved Transformer for High-Resolution GANs
PGMGAN	21.73	Partition-Guided GANs
PR-BigGAN - Precision	20.76	-
BigGAN-OBRS	11.65	Optimal Budgeted Rejection Sampling for Generative Models
PR-BigGAN - Recall	9.92	-
BigGAN	8.7	Large Scale GAN Training for High Fidelity Natural Image Synthesis
DiffAugment-BigGAN	6.8	Differentiable Augmentation for Data-Efficient GAN Training
CR-BigGAN	6.66	Consistency Regularization for Generative Adversarial Networks
LeCAM + DA	6.54	Regularizing Generative Adversarial Networks under Limited Data
BigGAN-deep	5.7	Large Scale GAN Training for High Fidelity Natural Image Synthesis
TarFlow	5.03	Normalizing Flows are Capable Generative Models
CDM	3.52	Cascaded Diffusion Models for High Fidelity Image Generation
ADM-G	2.97	Diffusion Models Beat GANs on Image Synthesis
BIGRoC-pl (Guided-Diffusion)	2.77	BIGRoC: Boosting Image Generation via a Robust Classifier
RIN	2.75	Scalable Adaptive Computation for Iterative Generation
BIGRoC-gt (Guided-Diffusion)	2.53	BIGRoC: Boosting Image Generation via a Robust Classifier
Poly-INR	2.08	Polynomial Implicit Neural Representations For Large Diverse Datasets
StyleGAN-XL	1.81	StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets
VDM++	1.75	-

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