11 datasets found

Text-to-image synthesis using Factor Decomposed Generative Adversarial Networks (FDGAN)

AttnGAN: Fine-grained text to image generation with attentional generative adversarial networks

Recipe1M and CUB datasets for text-to-image synthesis

The dataset used in the paper is the Pick-a-Pic dataset, which consists of 87,687 pairs of text prompts and images.

The dataset used in the paper is the PartiPrompts dataset, which consists of 851,293 pairs of text prompts and images.

The dataset used in the paper is a text-to-image synthesis dataset.

The dataset used in the paper "Scaling Laws of Synthetic Images for Model Training". The dataset is used for supervised image classification and zero-shot classification tasks.

Large-scale text-to-image diffusion models can gener-ate high-fidelity images with powerful compositional ability. However, these models are typically trained on an enormous...

A dataset of Creative-Commons-licensed images, which is used to train a set of open diffusion models that are qualitatively competitive with Stable Diffusion 2 (SD2).

The DrawBench dataset is a benchmark for text-to-image synthesis, consisting of images with multiple subjects and objects.

AvatarVerse is a stable pipeline for generating expressive high-quality 3D avatars from text descriptions and pose guidance.