The field of visual computing is rapidly advancing due to the emergence of generative
artificial intelligence (AI), which unlocks unprecedented capabilities for the generation …

We present SDXL, a latent diffusion model for text-to-image synthesis. Compared to
previous versions of Stable Diffusion, SDXL leverages a three times larger UNet backbone …

Abstract We introduce Adversarial Diffusion Distillation (ADD), a novel training approach that
efficiently samples large-scale foundational image diffusion models in just 1–4 steps while …

Diffusion models have recently gained unprecedented attention in the field of image
synthesis due to their remarkable generative capabilities. Notwithstanding their prowess …

Diffusion models have revolutionized text-to-image generation with its exceptional quality
and creativity. However, its multi-step sampling process is known to be slow, often requiring …

Diffusion models have achieved great success in synthesizing high-quality images.
However generating high-resolution images with diffusion models is still challenging due to …

Contemporary models for generating images show remarkable quality and versatility.
Swayed by these advantages the research community repurposes them to generate videos …

Text-to-image diffusion models have demonstrated remarkable capabilities in transforming
text prompts into coherent images yet the computational cost of the multi-step inference …

Large foundation models, including large language models (LLMs), vision transformers
(ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine …

The deployment of large-scale text-to-image diffusion models on mobile devices is impeded
by their substantial model size and high latency. In this paper, we present MobileDiffusion …