9 datasets found

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a large-scale text-to-image model to generate images with multiple subjects.

MARS is an innovative auto-regressive framework that not only retains the capabilities of pre-trained Large Language Models (LLMs) but also incorporates top-tier text-to-image...

Text-to-image Latent Diffusion model, CLIP model, Blended Diffusion model, GLIDE model, GLIDE-filtered model

The dataset used for testing the Concept Sliders, consisting of paired image data and text prompts.

The dataset used for training the Concept Sliders, consisting of paired image data and text prompts.

The authors present a photorealistic text-to-image diffusion model with deep language understanding.

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...

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