As one of the most popular and sought-after generative models in the recent years, diffusion
models have sparked the interests of many researchers and steadily shown excellent …

We introduce the Multi-Instance Generation (MIG) task, which focuses on generating
multiple instances within a single image, each accurately placed at predefined positions with …

In this paper, we introduce StableGarment, a unified framework to tackle garment-centric
(GC) generation tasks, including GC text-to-image, controllable GC text-to-image, stylized …

Recent advancements in text-to-image generation models have dramatically enhanced the
generation of photorealistic images from textual prompts, leading to an increased interest in …

Despite the recent advances in personalized text-to-image (P-T2I) generative models, it
remains challenging to perform finetuning-free multi-subject-driven T2I in a resource …

Diffusion models have significantly improved the performance of image editing. Existing
methods realize various approaches to achieve high-quality image editing, including but not …

With the advance of diffusion models, various personalized image generation methods have
been proposed. However, almost all existing work only focuses on either subject-driven or …

Food image composition requires the use of existing dish images and background images to
synthesize a natural new image, while diffusion models have made significant …

The increasing demand for controllable outputs in text-to-image generation has spurred
advancements in multi-instance generation (MIG), allowing users to define both instance …

Abstract Text-to-image (T2I) diffusion models have shown significant success in
personalized text-to-image generation, which aims to generate novel images with human …