2 citations · 3 across the 8 of their papers we have counts for
9 papers
SSR-Merge: Subspace Signal Routing for Training-Free LoRA Merging in Diffusion Models
Zhengxuan Wei, Yi Dong, Zonghui Li +6
Low-Rank Adaptation (LoRA) merging can efficiently combine diverse generative capabilities from multiple trained LoRAs for a diffusion model. However, existing LoRA merging techniq…
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…
RAP-SR: RestorAtion Prior Enhancement in Diffusion Models for Realistic Image Super-Resolution
Jiangang Wang, Qingnan Fan, Jinwei Chen +3
Benefiting from their powerful generative capabilities, pretrained diffusion models have garnered significant attention for real-world image super-resolution (Real-SR). Existing di…
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…
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…
Tuning-Free Adaptive Style Incorporation for Structure-Consistent Text-Driven Style Transfer
Yanqi Ge, Jiaqi Liu, Qingnan Fan +6
In this work, we target the task of text-driven style transfer in the context of text-to-image (T2I) diffusion models. The main challenge is consistent structure preservation while…
InstructBrush: Learning Attention-based Instruction Optimization for Image Editing
Ruoyu Zhao, Qingnan Fan, Fei Kou +7
In recent years, instruction-based image editing methods have garnered significant attention in image editing. However, despite encompassing a wide range of editing priors, these m…
DiffFAE: Advancing High-fidelity One-shot Facial Appearance Editing with Space-sensitive Customization and Semantic Preservation
Qilin Wang, Jiangning Zhang, Chengming Xu +7
Facial Appearance Editing (FAE) aims to modify physical attributes, such as pose, expression and lighting, of human facial images while preserving attributes like identity and back…