5 papers · 1 filter
Textualize Visual Prompt for Image Editing via Diffusion Bridge
Pengcheng Xu, Qingnan Fan, Fei Kou +5
Visual prompt, a pair of before-and-after edited images, can convey indescribable imagery transformations and prosper in image editing. However, current visual prompt methods rely…
CoMPaSS: Enhancing Spatial Understanding in Text-to-Image Diffusion Models
Gaoyang Zhang, Bingtao Fu, Qingnan Fan +5
Text-to-image (T2I) diffusion models excel at generating photorealistic images but often fail to render accurate spatial relationships. We identify two core issues underlying this…
AuthFace: Towards Authentic Blind Face Restoration with Face-oriented Generative Diffusion Prior
Guoqiang Liang, Qingnan Fan, Bingtao Fu +3
Blind face restoration (BFR) is a fundamental and challenging problem in computer vision. To faithfully restore high-quality (HQ) photos from poor-quality ones, recent research end…
LIPE: Learning Personalized Identity Prior for Non-rigid Image Editing
Aoyang Liu, Qingnan Fan, Shuai Qin +2
Although recent years have witnessed significant advancements in image editing thanks to the remarkable progress of text-to-image diffusion models, the problem of non-rigid image e…
FreeDiff: Progressive Frequency Truncation for Image Editing with Diffusion Models
Wei Wu, Qingnan Fan, Shuai Qin +3
Precise image editing with text-to-image models has attracted increasing interest due to their remarkable generative capabilities and user-friendly nature. However, such attempts f…