Diffusion model-based image editing: A survey

Y Huang, J Huang, Y Liu, M Yan, J Lv, J Liu… - ar** across sharp shape differences
C Zhu, K Li, Y Ma, L Tang, C Fang, C Chen… - ar** (CCS) enable a text-to-image model to
swap a concept in the source image with a customized target concept. However, the existing …

A Survey of Multimodal-Guided Image Editing with Text-to-Image Diffusion Models

X Shuai, H Ding, X Ma, R Tu, YG Jiang… - arxiv preprint arxiv …, 2024 - arxiv.org
Image editing aims to edit the given synthetic or real image to meet the specific requirements
from users. It is widely studied in recent years as a promising and challenging field of …

Distributionally Robust Graph Out-of-Distribution Recommendation via Diffusion Model

C Zhao, E Yang, Y Liang, J Zhao, G Guo… - arxiv preprint arxiv …, 2025 - arxiv.org
The distributionally robust optimization (DRO)-based graph neural network methods
improve recommendation systems' out-of-distribution (OOD) generalization by optimizing the …

Uncovering Vision Modality Threats in Image-to-Image Tasks

H Cheng, E **ao, J Yang, J Cao, Q Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
Current image generation models can effortlessly produce high-quality, highly realistic
images, but this also increases the risk of misuse. In various Text-to-Image or Image-to …

Exploring the latent space of diffusion models directly through singular value decomposition

L Wang, B Gao, Y Li, Z Wang, X Yang… - arxiv preprint arxiv …, 2025 - arxiv.org
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 …