HyperAIHyperAI

Text To Image Generation On Cub

Métriques

FID

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
FID
Paper TitleRepository
TLDM6.72Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders-
Attention-driven Generator (perceptual loss)-Controllable Text-to-Image Generation-
MirrorGAN-MirrorGAN: Learning Text-to-image Generation by Redescription-
GALIP10.08GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis-
GAWWN67.22Learning What and Where to Draw-
AttnGAN-AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
AttnGAN+CL16.34Improving Text-to-Image Synthesis Using Contrastive Learning-
VQ-Diffusion-F10.32Vector Quantized Diffusion Model for Text-to-Image Synthesis-
Lafite10.48LAFITE: Towards Language-Free Training for Text-to-Image Generation-
StackGAN-v215.3StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks-
Swinv2-Imagen9.78Swinv2-Imagen: Hierarchical Vision Transformer Diffusion Models for Text-to-Image Generation-
VQ-Diffusion-S12.97Vector Quantized Diffusion Model for Text-to-Image Synthesis-
StackGAN-v151.89StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks-
DM-GAN-DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis-
RAT-Diffusion6.36Data Extrapolation for Text-to-image Generation on Small Datasets-
StackGAN-StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks-
VQ-Diffusion-B11.94Vector Quantized Diffusion Model for Text-to-Image Synthesis-
RAT-GAN10.21Recurrent Affine Transformation for Text-to-image Synthesis-
DM-GAN+CL14.38Improving Text-to-Image Synthesis Using Contrastive Learning-
DF-GAN-DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis-
0 of 20 row(s) selected.