Large text-to-image models achieved a remarkable leap in the evolution of AI, enabling high-
quality and diverse synthesis of images from a given text prompt. However, these models …

Text-to-image generative models often reflect the biases of the training data, leading to
unequal representations of underrepresented groups. This study investigates inclusive text …

Recent text-to-image diffusion models have demonstrated an astonishing capacity to
generate high-quality images. However, researchers mainly studied the way of synthesizing …

Large-scale text-to-image generative models have been a revolutionary breakthrough in the
evolution of generative AI, synthesizing diverse images with highly complex visual concepts …

Personalized text-to-image generation using diffusion models has recently emerged and
garnered significant interest. This task learns a novel concept (eg, a unique toy), illustrated …

Diffusion-based models have achieved state-of-the-art performance on text-to-image
synthesis tasks. However, one critical limitation of these models is the low fidelity of …

Abstract Text-to-image (T2I) research has grown explosively in the past year owing to the
large-scale pre-trained diffusion models and many emerging personalization and editing …

Recently, diffusion models have achieved remarkable success in text-to-image generation,
enabling the creation of high-quality images from text prompts and various conditions …

Existing text-to-image diffusion models struggle to synthesize realistic images given dense
captions, where each text prompt provides a detailed description for a specific image region …

Text-to-image models offer a new level of creative flexibility by allowing users to guide the
image generation process through natural language. However, using these models to …