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Multiple Subjects Generation
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: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis
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... -
Laion-400M
Text-to-image Latent Diffusion model, CLIP model, Blended Diffusion model, GLIDE model, GLIDE-filtered model -
Concept Sliders Test Dataset
The dataset used for testing the Concept Sliders, consisting of paired image data and text prompts. -
Concept Sliders Dataset
The dataset used for training the Concept Sliders, consisting of paired image data and text prompts. -
Photorealistic text-to-image diffusion models with deep language understanding
The authors present a photorealistic text-to-image diffusion model with deep language understanding. -
Ablating Concepts in Text-to-Image Diffusion Models
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...
