Image restoration (IR) has been an indispensable and challenging task in the low-level
vision field, which strives to improve the subjective quality of images distorted by various …

Text-to-image diffusion models can create stunning images from natural language
descriptions that rival the work of professional artists and photographers. However, these …

Generative Large Language Models (LLMs) have demonstrated remarkable results for a
wide range of tasks. However, deploying these models for inference has been a significant …

Large foundation models, including large language models, vision transformers, diffusion,
and large language model based multimodal models, are revolutionizing the entire machine …

Diffusion models have recently dominated image synthesis and other related generative
tasks. However, the iterative denoising process is expensive in computations at inference …

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

During image editing, existing deep generative models tend to re-synthesize the entire
output from scratch, including the unedited regions. This leads to a significant waste of …

Diffusion models have been proven highly effective at generating high-quality images.
However, as these models grow larger, they require significantly more memory and suffer …

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

Abstract Text-to-image (T2I) generation with Stable Diffusion models (SDMs) involves high
computing demands due to billion-scale parameters. To enhance efficiency, recent studies …