Text To Image Generation On Cub

Metrics

FID

Results

Performance results of various models on this benchmark

Model Name	FID	Paper Title	Repository
TLDM	6.72	Truncated 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	-
GALIP	10.08	GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis	-
GAWWN	67.22	Learning What and Where to Draw	-
AttnGAN	-	AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks	-
AttnGAN+CL	16.34	Improving Text-to-Image Synthesis Using Contrastive Learning	-
VQ-Diffusion-F	10.32	Vector Quantized Diffusion Model for Text-to-Image Synthesis	-
Lafite	10.48	LAFITE: Towards Language-Free Training for Text-to-Image Generation	-
StackGAN-v2	15.3	StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks	-
Swinv2-Imagen	9.78	Swinv2-Imagen: Hierarchical Vision Transformer Diffusion Models for Text-to-Image Generation	-
VQ-Diffusion-S	12.97	Vector Quantized Diffusion Model for Text-to-Image Synthesis	-
StackGAN-v1	51.89	StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks	-
DM-GAN	-	DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis	-
RAT-Diffusion	6.36	Data Extrapolation for Text-to-image Generation on Small Datasets	-
StackGAN	-	StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks	-
VQ-Diffusion-B	11.94	Vector Quantized Diffusion Model for Text-to-Image Synthesis	-
RAT-GAN	10.21	Recurrent Affine Transformation for Text-to-image Synthesis	-
DM-GAN+CL	14.38	Improving Text-to-Image Synthesis Using Contrastive Learning	-
DF-GAN	-	DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis	-

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