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Image Generation On Ffhq 256 X 256

Metrics

FID

Results

Performance results of various models on this benchmark

Model Name
FID
Paper TitleRepository
GANFormer7.42Generative Adversarial Transformers-
BigGAN11.48A U-Net Based Discriminator for Generative Adversarial Networks-
CLR-GAN3.37CLR-GAN: Improving GANs Stability and Quality via Consistent Latent Representation and Reconstruction
StyleNAT2.05StyleNAT: Giving Each Head a New Perspective-
StyleGAN2-ada (Exposing)5.30Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models-
StyleGAN-XL (DINOv2)-StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets-
LDM8.11--
INR-GAN-bil4.95Adversarial Generation of Continuous Images-
Anycost GAN3.35Anycost GANs for Interactive Image Synthesis and Editing-
R3GAN2.75The GAN is dead; long live the GAN! A Modern GAN Baseline
LeCAM (StyleGAN2 + ADA)3.49Regularizing Generative Adversarial Networks under Limited Data-
Efficient-VDVAE34.88Efficient-VDVAE: Less is more-
LDM (Exposing)8.11Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models-
Unleashing Transformers (DINOv2)-Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes-
InsGen (DINOv2)-Data-Efficient Instance Generation from Instance Discrimination-
HiT-S3.06Improved Transformer for High-Resolution GANs-
HiT-L2.58Improved Transformer for High-Resolution GANs-
Very Deep VAE-Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images-
StyleSwin2.81StyleSwin: Transformer-based GAN for High-resolution Image Generation-
InsGen (Exposing)3.46Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models-
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Image Generation On Ffhq 256 X 256 | SOTA | HyperAI