Denoising diffusion models have emerged as a powerful tool for various image generation
and editing tasks, facilitating the synthesis of visual content in an unconditional or input …

Generating instructional images of human daily actions from an egocentric viewpoint serves
as a key step towards efficient skill transfer. In this paper, we introduce a novel problem …

The inversion of diffusion model sampling, which aims to find the corresponding initial noise
of a sample, plays a critical role in various tasks. Recently, several heuristic exact inversion …

Conditional image synthesis based on user-specified requirements is a key component in
creating complex visual content. In recent years, diffusion-based generative modeling has …

Despite the groundbreaking success of diffusion models in generating high-fidelity images,
their latent space remains relatively under-explored, even though it holds significant promise …

Diffusion models have become a cornerstone in image editing, offering flexibility with
language prompts and source images. However, a key challenge is attribute leakage, where …

We present DiffChat, a novel method to align Large Language Models (LLMs) to" chat" with
prompt-as-input Text-to-Image Synthesis (TIS) models (eg, Stable Diffusion) for interactive …